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Theses and Dissertations

6-15-2018

Emotional Overtones Of Professional Jargon As Experienced By Emotional Overtones Of Professional Jargon As Experienced By

English And Bilingual Speakers English And Bilingual Speakers

Daisy Bueno Illinois State University, daisybueno2@gmail.com

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Recommended Citation Recommended Citation Bueno, Daisy, "Emotional Overtones Of Professional Jargon As Experienced By English And Bilingual Speakers" (2018). Theses and Dissertations. 950. https://ir.library.illinoisstate.edu/etd/950

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EMOTIONAL OVERTONES OF PROFESSIONAL JARGON AS EXPERIENCED BY

ENGLISH AND BILINGUAL SPEAKERS

Daisy Bueno

97 Pages

Previous research has suggested that technical language is regularly used in the area of

clinical practice called Applied Behavior Analysis (ABA). However, the use of this technical

language or jargon may elicit unpleasant emotional responses that could be expected to “turn

off” clients or parents of child clients. To understand how emotional overtones of words may

interfere with therapist-client communication, the current study utilized an online data collection

tool to obtain word emotion ratings of jargon words and terms. The first study is a replication

and extension of past research that used existing word emotion ratings for ABA jargon words

from a larger corpus of English words. I collected novel emotional ratings of ABA terms and

General Psychological terms used in clinical settings. The second study examined emotional

responses to ABA terms and General Psychological terms in both English and Spanish by

bilingual individuals. Participants completed a word rating task and an acculturation scale that

assessed their level of bilingualism. The results of Study 1 are consistent with previous research

in finding that ABA jargon terms were generally perceived as unpleasant. General Psychological

terms were found to be just as unpleasant as ABA terms. Although previous research has shown

that bilingual individuals may express emotions differently depending on which language they

are using at the time, in Study 2 I found that bilingual individuals rated ABA terms and General

Psychological terms as largely equivalent with respect to emotional response in both English and

Spanish. Language dominance and language preference were not correlated with emotional

responses to specific terms in either language. Together the results of these studies inform

decisions about how to communicate technical information about therapy to individuals seeking

support from therapists.

KEYWORDS: Jargon, Applied Behavior Analysis, Word Emotion, Bilingualism

EMOTIONAL OVERTONES OF PROFESSIONAL JARGON AS EXPERIENCED BY

ENGLISH AND BILINGUAL SPEAKERS

DAISY BUENO

A Dissertation Submitted in Partial Fulfillment of the Requirements

for the Degree of

DOCTOR OF PHILOSOPHY

Department of Psychology

ILLINOIS STATE UNIVERSITY

2018

© 2018 Daisy Bueno

EMOTIONAL OVERTONES OF PROFESSIONAL JARGON AS EXPERIENCED BY

ENGLISH AND BILINGUAL SPEAKERS

DAISY BUENO

COMMITTEE MEMBERS:

Thomas Critchfield, Co-Chair

Corinne Zimmerman, Co-Chair

Karla J. Doepke

Beth Hatt

i

ACKNOWLEDGMENTS

I wish to thank my committee members, Karla Doepke and Beth Hatt, for their feedback

and support on this project. I would especially like to thank my Co-Chairs: Tom Critchfield, for

helping me develop my small ideas into this dissertation, and Corinne Zimmerman, for all the

“cool-whip” days and nights, all the cookies and coffee, and the endless time and support. I do

not think the right words to express my gratitude exist -- I even tried to Google it!

Steve and Jillian, thanks for all the proofreading and for making sure I knew how to

count. To all my friends and loved ones, who answered panicked questions, sent me messages of

encouragement, and fed me tacos, I owe you billions! I can’t forget Lilly and Patton, thanks for

all the puppy cuddles!

Ultimamente, le quiero dedicar esta tesis y toda mi educacción a mi familia. Gracias por

todo el apoyo y paciencia todos estos años. Todo fue por ustedes y para ustedes.

D.B.

ii

CONTENTS

Page

ACKNOWLEDGMENTS i

CONTENTS ii

FIGURES iv

CHAPTER I: THE PROBLEM AND ITS BACKGROUND 1

CHAPTER II: REVIEW OF THE LITERATURE 3

Jargon in Applied Behavior Analysis 3 Linguistic Diversity Challenges 7 Word Emotion 8 Emotional Responses to ABA Jargon 11 The Current Study 12 CHAPTER III: STUDY 1 13

Method 14 Participants 14 Measures 15 Procedure 17 Results 19 Data Trimming 19 Research Questions 20 Study 1 Discussion 27 CHAPTER IV: STUDY 2 32

Bilingualism and Word Emotion 32 Method 34

Participants 34 Measures 35 Materials 36 Design and Procedures 36 Results 36

iii

Language Preference and Descriptive Statistics 36 Research Questions 37 Study 2 Discussion 40 CHAPTER V: CONCLUSIONS 43

General Discussion 43 Strengths and Limitations of the Current Study 47 Directions for Future Research 50 Clinical Implications 51 REFERENCES 55

APPENDIX A: SHORT ACCULTURATION SCALE 61

APPENDIX B: INSTRUCTIONS FOR WORD RATING TASK 63

APPENDIX C: DEMOGRAPHICS 65

APPENDIX D: TABLES 68

iv

FIGURES

Figure Page

1.! Thirteen ABA words with established norms from the Warriner et al. (2013) corpus that were selected for analysis by Critchfield et al. (2017) and rated in the current study and how they were classified 22

2.! General psychological terms (n = 26) with established norms from the Warriner

et al. (2013) corpus and the current study and how they were classified 23

3.! ABA terms (n = 36) categorized by high and low valence and high and low arousal assigned to each of the four categories of the valence-arousal scatterplot developed by Critchfield et al. (2017) 24

4.! General Psychological terms (n = 33) categorized by high and low valence and high

and low arousal assigned to each of the four categories of the valence-arousal scatterplot developed by Critchfield et al. (2017) 25

5.! Percentages of ABA technical terms and General Psychological terms that fall into

each of the four quadrants of a valence-arousal scatterplot 26

1

CHAPTER I: THE PROBLEM AND ITS BACKGROUND

Jargon typically refers to the specialized vocabulary that a specific community uses for a

more efficient method of communication among themselves. Jargon may help individuals

communicate with precision, meaning, and confidence, but jargon terms are typically not clear to

those outside the specialized area (Hallenstein, 1978). By using jargon, individuals are able to

use a word or short phrase to express an otherwise much longer explanation. Hallenstein also

suggested that jargon use in a specialized group gives that community a sense of identity, as it

helps identify members of an in-group who shares similar values.

A problem, however, arises when individuals from the in group of a specialized or

professional community are required to communicate with individuals who are not a part of the

group. Although individuals from a specific in-group may feel more comfortable engaging in

conversations with individuals who share their values, beliefs, educational experiences, and

technical vocabulary, there is usually a need to communicate with members outside of the group.

A well-known example occurs when physicians attempt to interact with their patients (Ha, Anat,

& Longnecker, 2010). Other examples include the need for scientists to communicate with the

media, policy makers, and other members of the public (e.g., Goldman & Bisanz, 2002).

Of particular relevance to the present investigation is the situation that occurs when

professional mental health caregivers interact with clients, or with the parents, families, or

teachers of child clients (e.g., Elliot, 1988). Such individuals may not understand the technical

language used within the specialized areas in mental health (e.g., Applied Behavior Analysis). In

such cases, jargon can be a barrier to clear communication, and it can make for a one-directional

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“conversation” that hinders the development of a productive professional relationship with

individuals outside of the in-group.

Additionally, it is important to note the continuous changes in demographics of the

United States. The Bilingual (Spanish-English speaking) population is growing. As such, there is

likely to be an increase in the number of Bilingual clients needing support and mental health

services with a corresponding increase in the need for Bilingual therapists. It is therefore

important to consider the emotional overtones that specific jargon terms have in each language to

encourage the best communication with clients who need support.

In the current study, I directly examined the emotional reactions that individuals have to

ABA jargon and General Psychological jargon. Previous research has examined the emotional

reactions to jargon using existing corpora. Critchfield, Becirevic, and Reed (2017) suggested that

for a more thorough examination of emotional responses, it is important to collect novel ratings

of terms. The current study represents an extension of this previous work by collecting novel

valence and arousal ratings and comparing the results to previous research. Additionally,

Critchfield and Doepke (2018) identified the need for cross-language studies on the acceptance

of ABA technical vocabulary. A second study examined the emotional responses Bilingual

(Spanish-English) individuals have to mental health technical jargon in both languages.

In the review of the literature I first discuss the use of jargon in ABA. I then discuss

linguistic diversity challenges within the field of mental health. I also provide a background on

previous word emotion research including previous research related to emotional responses to

ABA jargon.

3

CHAPTER II: REVIEW OF THE LITERATURE

Jargon in Applied Behavior Analysis

Applied Behavior Analysis (ABA) arose in the 1950s and 1960s from basic research on

learning and is an approach to human services based on manipulating the environmental context

to help increase prosocial behaviors (Ayllon & Michael, 1959). Contrary to many other

approaches that view disordered behavior as a side effect of psychopathological causes or

disordered thinking, ABA focuses on experimentally manipulating the environment to directly

decrease maladaptive behaviors such as self-injury and aggression (Durand, 1987). The field of

ABA exists to remediate problem behavior in a direct, systematic, experimental, and

individualized manner and encourage positive social behaviors in society (Baer, Wolf, & Risley,

1968; Jacobson & Holburn, 2004).

Although ABA is well established as an effective, evidence-based approach (e.g.,

National Autism Center, 2015), the image of applied behavior analysts among individuals

outside the field is not always a positive one. A variety of observers within the field have

suggested that applied behavior analysis has a “marketing problem” (Bailey, 1991, p. 447) in

which its practitioners and interventions are viewed as unpleasant and/or undesirable. It is widely

thought that one component of this problem is a technical vocabulary that is not user-friendly to

individuals outside the field (Bailey, 1991; Foxx, 1996; Lindsley, 1991). For example, Foxx

(1996) stated “our desire for precision in language and discourse has led to the perception that

we are arrogant and abrasive” (p. 149). Individuals in the field of ABA are notorious for

communicating about human behavior with terminology that is understood only by members

within the field. For instance, the production and dissemination of data guides the decision-

4

making process of individuals in the field of ABA. This focus on empirical data and evidence

can lead behavior analysts to speak of “subjects,” “control conditions,” and “independent

variables,” and although such terms have precise meanings in the world of behavioral

measurement, they may not be perceived by clients (or parents of child clients) as socially

acceptable (Bailey, 1991). Specifically, it has been hypothesized that the terminology used to

describe the experimental science process can be perceived as cold and manipulative, a

suggestion that is broadly consistent with unflattering descriptions of applied behavior analysts

by individuals outside the field such as Maurice (1993), whose daughter received ABA therapy.

There are at least two possible reasons for these perceptions. First, individuals who are

not familiar with the field of ABA simply may not understand the specific meaning of the

technical terms used by practitioners or clinicians in this field, causing them to remain

uninformed about what applied behavior analysts propose to do, and why (i.e., it is an

“information deficit”). From this perspective, the problem is that jargon lacks meaning. Second,

Foxx (1996) pointed out that behavior analysis terms might hold a different meaning to

individuals outside the field than they do to individuals in the field of ABA. For example,

“punishment” is a term regularly used in the field of ABA to describe a method of decreasing a

non-desired behavior. However, as will be explained below, this word typically has different

connotations for consumers of ABA interventions.

The reason for conflicting interpretations of technical terms may be traced to the way

behavior analysis terms were coined in the first place. Harzem and Miles (1978) pointed out that

the language used by behavior analysts has been created by “conceptual revision.” Rather than

coining new words for technical purposes, behavior analysts have often assigned a new meaning

to an existing word (Harzem & Miles, 1978). Researchers in the field of science education

5

discuss a similar problem with the use of labels such as “direct instruction” or “discovery

learning” when media outlets report the results of research to the lay public. For instance, Klahr

and Li (2005) stated, “when we adopt a widely used terminology, we are burdened with ensuring

that our implementation is consistent with the term’s meaning in the educational community” (p.

253). In this example, researchers and media sources translated “direct instruction” to mean

“passive learning.” Deitz and Arrington (1983) also argued that the words “extinction” and

“punishment” are borrowed words with clear technical definitions but rather often unpleasant

everyday connotations. In behavior analysis, extinction is the weakening of a behavior that

results when reinforcement ceases, but in the public mind, as in biology, extinction is the

elimination of a species (Foxx, 1996). In behavior analysis, punishment is when a behavior-

caused event (i.e., consequence) results in that behavior stopping or occurring less often. In

everyday language, punishment is used to denote “suffering, pain, or loss that serves as

retribution, or a penalty inflected on an offender through judicial procedure, and severe, rough or

disastrous treatment” (Webster’s Ninth Collegiate Dictionary, 1987). The dual meanings of such

terms (Foxx, 1996) lead to a type of ambiguity that can adversely affect the bidirectional

communication that is meant to help decrease problem behaviors through the use of behavioral

principles. As yet another example, the term “consequences” almost always has an unpleasant

connotation among the general public.

As a discipline, behavior analysis shares with various fields (e.g., education, medicine)

the goal of positively influencing people’s quality of life (Bailey, 1991). However, in the pursuit

of this goal, behavior analysts strive to be science-driven and evidence-based, which means the

field has a deep grounding in technical concepts and vocabulary. Bailey argued that linguistic

habits that trace back to the field’s laboratory roots have adverse effects on the pursuit of

6

promoting everyday well-being. Applied behavior analysts may mistakenly believe that in using

technical language that they are bolstering the field’s credibility as science-based. But this

attention to increasing the credibility and focus of science may actually distract from recognizing

the need to develop effective “marketing” strategies that acknowledge human values in language

that individuals outside the field of ABA can easily understand. For instance, Bailey (1991)

pointed out that applied behavior analysts, in mimicking the linguistic habits of behavior

scientists, may refer to those they work with as “subjects” and discuss interventions using terms

like “control,” “manipulate,” and “intervention.” To individuals who are not familiar with the

meaning of ABA terminology, these terms can sound unpleasant and coercive and are unlikely to

recruit buy-in from clients seeking behavioral support. Bailey’s (1991) central point may be

summarized as follows: The tools of applied behavior analysis are intended to benefit all

individuals, but not all individuals are likely to regard behavior analysts as the sort of people in

whom they prefer to place their trust.

Consistent with these worries, several studies suggest that potential clients regard ABA

services as less acceptable when they are described using jargon as when they are described

using everyday language (e.g., Becirevic, Critchfield, & Reed, 2016; Jarmolowicz et al., 2008;

Witt, Moe, Gutkin, & Andrews, 1984). Jarmolowicz et al. (2008) also found that

paraprofessionals who were taught an intervention using jargon did a worse job of implementing

it than did peers who were taught using plain English. These studies do not show why jargon is

problematic but support the assumption that jargon has potential adverse effects on the

“marketing” and dissemination of ABA.

7

Linguistic Diversity Challenges

In evaluating the challenges of speaking pleasantly and clearly about applied behavior

analysis, it is important to keep in mind that psychology as a discipline is a highly culture-bound

mainstream European-American phenomenon (Hall, 2001). This insight has many implications,

but in general it is deemed to be important for clinicians to develop an awareness of cultural

differences and to adapt modes of therapy to respect and harness these differences (e.g., Bolling,

2002; Hall, 2001).

One domain of clear relevance concerns the native language(s) that clients speak. For

example, the largest minority group in the United States is Latinx population. According to the

Pew Research Center’s (2013) National Survey of Latinos, 36% are bilingual, 25% mainly use

English, and 30% mainly use Spanish. Among those who speak English, 59% are bilingual (Pew

Research Center, 2013).

As ethnic and cultural diversity continues to increase in the United States, it is important

to be able to translate the research and practices of ABA therapy in a culturally and linguistically

sensitive manner. If, however, English-speaking clients exhibit difficulties understanding

relevant theories and concepts related to ABA, then it can be safe to assume that individuals with

other native languages may have similar difficulties.

Although no actuarial statistics are available, casual observation suggests that most

therapists trained in ABA are native English speakers. This implies a limited capacity to

communicate with non-native English speakers. Research suggests that in the United States,

Latinx children with ASD are under-identified or identified at a later age than children of

English-speaking families (Zuckerman et al., 2013). This trend may well result from a shortage

of Spanish-speaking or Bilingual ABA therapists and pediatricians, and likely results in Latinx

8

children with ASD not receiving the early intervention services that researchers have shown are

most effective (Reichow, 2012). As the number of Latinx children diagnosed with ASD and

other developmental disorders continues to increase, it is important to be able to communicate

the necessary information about interventions in Spanish as well as English.

Translating from one language to another can be a difficult skill to master, and in

therapeutic situations, the stakes for interpreting information clearly are high. In medical

situations, for example, English-speaking staff may need to rely on family members to help with

interpreting. But this can be problematic, in part because neither the patient nor the ad hoc

translators may be familiar with medical jargon. Large medical institutions and hospitals often

use phone services to quickly provide consumers with help in several languages, but once again,

those consumers may not understand the jargon that is used. Analogously, in the ABA

community, the first systematic effort at addressing translation problems was undertaken by the

Behavior Analyst Certification Board® (BACB), which produces glossaries of technical terms in

several languages, including Spanish (https://www.bacb.com/wp-content/uploads/2017/09/

Spanish-English-ABA-Glossary.pdf). However, these glossaries say nothing about how

consumers might actually understand or experience these terms (Critchfield & Doepke, 2018).

Word Emotion

As mentioned previously, jargon could have at least two independent effects on listeners

who are not familiar with the field of ABA: First, an individual may not understand (or may

misunderstand) the meaning of jargon. Second, an individual may understand jargon terms, but

in ways that are separate from their intended meaning. Moreover, such terms may evoke

emotional reactions that are separate from explicit word meaning (Foxx, 1996). That is, the

connotation of a word (i.e., the emotional association surrounding the word) may have an impact

9

on the denotation of a word (i.e., the strict dictionary meaning; Jay & Janschewitz, 2007). The

present investigation focuses on the emotional effects that words have.

Recognizing that words provide triggers to various emotional states, researchers have

developed methods of quantifying these states. Doing so has facilitated several lines of

investigation aimed at understanding: (a) the impact that emotional responses to words have on

processing and memory; (b) the way emotional responses to words affect subsequent behavior;

(c) the way emotional responses to individual words contribute to the overall sentiments

experienced through larger messages; and (d) the ways in which new words acquire emotional

properties (Warriner, Kuperman, & Brysbaert, 2013). For present purposes, however, the

primary interest is simply in measuring emotional responses to words.

To date, the procedures of most word-emotion studies have been based on Bradley and

Lang’s (1999) Affective Norms for English Words (ANEW) and its various translated versions

(e.g., Warriner et al., 2013). ANEW was developed to provide a set of normative emotional

ratings for words in the English language (Bradley & Lang, 1999). The goal of this research was

to have a set of verbal materials that has been rated in terms of three dimensions of emotion:

valence (ranging from pleasant to unpleasant), arousal (ranging from calm to excited), and

dominance (ranging from dominant to submissive) (see Osgood, Suci, & Tannenbaum, 1957;

Russell & Mehrabian, 1977). In the current investigation, I focused on both arousal and valence

in Study 1 and valence in Study 2. Arousal was measured because it is related to Skinner’s

(1953) description of emotions as motivating operations that make some behaviors more or less

reinforcing to engage in (Critchfield & Doepke, 2018). Furthermore, Warriner and Kuperman

(2015) suggested that arousal and valence interact to enhance each other to determine an overall

emotional response to words.

10

The original ANEW norms include ratings for 1,034 English words (Bradley & Lang,

1999) that were obtained using Self-Assessment Manikins (SAM), a form of rating scale

employing emotion-specific facial icons as response options instead of word anchors (see also

Dodds et al., 2015). Many other studies have used more traditional word-anchored rating scales,

and have produced results that correlate highly with the SAM ratings from ANEW (Warriner et

al., 2013).

Word emotion-rating procedures operate similarly for SAM and traditional Likert-type

scales. Raters are chosen for competence in the language under consideration, and are presented

with words one at a time. They are asked to indicate how each word makes them feel, and are

told to respond quickly and without deliberate thought in order to record their first gut-level

reaction. Norms consist of the means of ratings made by many individuals (e.g., 1,827 valid

responders in Warriner et al., 2013).

Although such procedures are relatively simple, they are given a measure of validity by

research showing that when people experience words in context -- as part of a larger message -- a

variety of reactions to the larger message are predictable from the ratings of the individual words

in it. For example, mean valence predicts that words that generally make people feel a sense of

happiness are easier to picture, concrete, familiar, and they are usually associated with low pain

(Warriner et al., 2013). Similarly, words that provide positive emotions can help communicate

persuasive messages. Mitchell, Brown, Morris-Villagran, & Villagran (2001) explained that an

important moderator of the effectiveness of persuasive messages is the emotion experienced by

the receiver of the message.

11

Emotional Responses to ABA Jargon

As previously discussed, it can be difficult to “market” ABA to clients in need of

behavioral services due to the technical language used in behavioral treatments, and this may be

due in part to emotional baggage carried by some of the words that function as ABA technical

terms. In order to assess the emotional responses individuals outside the field of ABA may have

to behavioral jargon used frequently in behavioral treatment, Critchfield et al. (2017) selected

words that behavior analysts use as technical terms and referenced them against normative word

emotion data provided by Warriner et al. (2013) and Dodds et al. (2015). They also obtained

normative word emotion data for words that are commonly used to discuss general science,

clinical work, and behavioral assessment. As expected based on concerns about the “marketing

problem,” ABA terms tended to score as more unpleasant than other professional terms, and

more unpleasant than English words generally (Critchfield et al., 2017). For example, ABA

terms such as “punishment” were rated as more unpleasant than science terms such as

“experiment.” This area of research is helpful in identifying how emotional responses to

behavioral jargon could interfere with treatment implementation and integrity.

Although most discussions of ABA’s “marketing problem” have concentrated on

English-language behavioral jargon, Critchfield and Doepke (2018) identified a need for cross-

language and cross-cultural studies on the acceptance of ABA and the role that its peculiar

technical vocabulary may play in the overall acceptability of the field. They used the same

method as Critchfield et al. (2017), using ABA terms from published norms in English and five

other languages. Critchfield and Doepke (2018) found some cross-language similarities: terms

that were perceived as pleasant (unpleasant) in English were perceived similarly in Spanish,

French, Portuguese, German, and Arabic. Critchfield and Doepke’s study included only a small

12

set of ABA terms because they examined published word-emotion corpora that included only

those words that double as ABA terms. Critchfield and Doepke pointed out that a more thorough

examination of the emotional properties of ABA terms in different languages will require

collecting novel ratings rather than relying on previously published corpora. This is the general

goal of the proposed investigation.

The Current Study

The goal of the current research was to evaluate whether word-emotion effects for ABA

terminology that have been documented in English in the analysis of existing word corpora apply

to perceptions of ABA jargon by English speakers and by bilingual speakers. Across two studies,

I evaluated a large sample of ABA terms to examine similarities and differences in emotional

responses to ABA terms in English and Spanish by bilingual speakers. Importantly, I collected

novel emotion ratings for a larger set of ABA terms with respect to both valence and arousal. In

Study 1, I examined responses to ABA terms and general psychological terms by English

speakers (Chapter III). In Study 2, I examined responses to ABA terms and general

psychological terms in English-Spanish bilinguals (Chapter IV).

13

CHAPTER III: STUDY 1

Previous research has examined word-emotion ratings for ABA terms. The current study

replicates and extends this work by (a) using a larger set of ABA terms (single words and

compound terms) than previous studies (e.g., Critchfield & Doepke, 2018), and (b) presenting

these terms to participants to rate rather than using existing corpora. As noted in Chapter II,

Critchfield and Doepke suggested that a more thorough examination of the emotional properties

of ABA terms in different languages would require collecting novel ratings rather than relying on

previously published corpora. Critchfield et al. (2017) plotted the ABA terms that exist in the

language corpora (some of which have alternative meanings, such as elopement or extinction). In

the present study, a context is established in which most of the terms are psychological or

clinical in nature, whereas in Warriner et al. (2013), the context was a large set of general

English words.

The specific research questions that I addressed in the first study are:

Research Question 1: How do mean emotional response ratings (valence) for ABA

technical terms and general psychological terms made by participants compare to normative

emotional response ratings (valence) for same-language words generally?

Research Question 2: How do mean emotional response ratings (valence and arousal) for

ABA technical terms made by participants compare to normative emotional response ratings

(valence and arousal) for the same terms for those available from the Warriner et al. (2013)

corpus that were analyzed by Critchfield et al. (2017)?

14

Research Question 3: How do emotional response ratings (valence and arousal) for ABA

technical terms compare to those for a set of general psychological terms related to clinical

practice but not to ABA specifically?

Method

Participants

Volunteers consisted of 237 volunteers that were recruited through mTURK; all were at

least 18 years of age and self-identified as monolingual English speakers. Participation was

restricted to individuals who reside in the United States. Those who completed the survey and

responded to attention check questions correctly were paid $1.00 for their participation. Each

participant completed either the valence task or the arousal task.

A total of 123 volunteers completed the valence task. Eleven individuals were eliminated

based on criteria set out by Warriner et al. (2013) that will be described in more detail in the

Results section below. This left 112 participants, 71 of whom were male (63.4%) and the

majority of whom identified as being White/Caucasian (n = 86; 76.8%). Nine participants

identified as Asian/Pacific Islander (8.0%), six identified as Multi-Racial/Multi-Ethnic (5.4%),

four identified as Black/African American (3.6%), and five identified as Hispanic/Latino (4.5%).

Two respondents preferred not to answer this question. Most participants had a Bachelor’s

Degree (n = 41; 36.6%) or Some College (n = 36, 63.4%). The average age was 37.06 years (SD

= 11.13). The majority did not have children (n = 72, 64.3%). Three participants (2.7%) reported

having at least one family member who had received behavioral (ABA) services in the past, and

two (1.8%) reported having at least one family member who was receiving behavioral (ABA)

services at the time the survey was completed.

15

A total of 114 volunteers completed the arousal task. Thirty-eight individuals were

eliminated from this rating task based on Warriner et al.’s criterion described below. This left 76

participants, approximately half of whom were male (n = 41; 53.9%) and the majority of whom

identified as White/Caucasian (n = 66, 86.8%). Three participants identified as Asian/Pacific

Islander (3.9%), three identified as Hispanic/Latino (3.9%), two identified as Black/African

American (2.6%), and two identified as Multi-Racial/Multi-Ethnic (2.6%). Most had completed

High School (n = 25; 32.9%) and Some College (n = 13; 17.1%). The average age was 37.71 (SD

= 11.10). The majority of participants did not have children (n = 51; 67.1%). Three participants

(3.9%). reported having at least one family member who had received behavioral (ABA) services

in the past and two participants (2.6%) reported having had at least one family member who was

receiving behavioral (ABA) services at the time the survey was completed.

Measures

Word lists. The 92 words/terms employed in the study were classified into one of four

categories: (a) calibrator words (n = 9), (b) general psychological terms (n = 33), (c) ABA

technical terms (n = 36), and (d) control words (n = 14). All calibrator and control words were

previously normed for emotional valence and arousal (Warriner et al., 2013), as were 26 of the

general psychology terms and 13 of the ABA technical terms. The nine calibrator words were

presented in a fixed sequence at the beginning of the survey. The calibrator words included terms

such as mechanic, accomplishment, and terrorism for the valence dimension and party, cat, and

meditation for the arousal dimensions. The calibrator words were chosen separately for each of

the two dimensions with the goal of providing participants practice with a large range of stimuli

before beginning the task and were selected from norming samples in English (Warriner et al.,

16

2013). The calibrator words presented the participants with an opportunity to use the whole

rating scale, as words were selected with norms that were high, middle, and low.

Thirty-three of the words were classified as general psychological terms used in clinical

practice and included words such as disorder, confidentiality, and addiction. Word emotion

ratings for 26 of these terms were identified from Warriner et al. (2013). Various other terms (or

short phrases) such as learned helplessness, substance abuse, and play therapy do not have

established norms. For the applied behavior analysis technical terms, 36 words or short phrases

were used. This list included the 13 terms used in the Critchfield and Doepke (2018) study for

which word-emotion rating norms were available and several terms consisting of short phrases

(e.g., preference assessment) for which no established norms were available, with the latter

selected from the BACB (2014) Spanish-English glossary.

Control words were included in order to serve as additional attention checks throughout

the survey. Control words included terms such as jail, joke, and sunshine for the valence list and

dangerous, emergency, and assault for the arousal list. These words were selected from the

norming studies by Warriner et al. (2013). The control words were interspersed randomly

throughout the list of ABA and general psychological terms to ensure respondents were

attending to the task. That is, if participants did not make ratings similar to the established norms

across this set of words (e.g., if “rampage” was rated as evoking positive emotions or “thrill” was

rated as calming) then those participants were eliminated from the final sample for data analysis

purposes (described in more detail below).

Rating scales. As in the norming studies by Warriner et al. (2013), participants worked

independently and were asked to evaluate terms, presented visually one at a time, on one of the

two emotional dimensions of interest. The anchors ranged from negative emotion to positive

17

emotion. Participants who completed the valence task rated the terms on a scale of 1 =

“Unhappy” to 9 = “Happy.” Those who completed the arousal task rated the terms on a scale of

1 = “Calm” to 9 = “Excited.”

Language use. Five items from the Acculturation Scale for Hispanics (Marin, Sabogal,

Marin, Otero-Sabogal, & Perez-Stable, 1987) were used to confirm that respondents were

monolingual English speakers. This scale includes a factor for “Language Use and Ethnic

Loyalty,” which includes five items that assess preference for using English versus Spanish for

reading and speaking as an adult, language use in childhood and at home, language use when

interacting with friends, and typical language used for thinking (see Appendix A). There are five

available responses to choose from: “Only Spanish,” “Spanish better than English,” “Both

Equally,” “English better than Spanish,” and “Only English.”

Procedure

Recruitment platform. Participants were recruited through Amazon Mechanical Turk

(mTurk), which has become a popular method for crowdsourcing recruitment and data collection

worldwide (Harms & DeSimone, 2015). Researchers develop "Human Intelligence Tasks"

(HITs), which can include surveys, experiments, and/or coding tasks, and pay a fee to volunteers

for completing them (Keith, Tay, & Harms, 2017). This method has created the opportunity for

researchers to collect data at a reduced cost and with samples showing greater diversity with

respect to education and age than the typical samples of college students used in psychological

research (Keith et al., 2017).

Following mTurk conventions, the current study was announced in the system via a one-

sentence study description accompanied by a description of inclusion/exclusion criteria and the

compensation amount being offered for completion ($1.00). To participate in the current study,

18

respondents were required to have completed at least 25 previous HITs and to have earned a HIT

Approval Rate of at least 80%, meaning they had successfully completed at least 80% of the

previous HITs for which they had volunteered.

Data collection platform. Individuals interested in participating in the study were

directed to a link into the Qualtrics® online survey platform. Although data can be collected

within MTurk, for present purposes an outside platform was employed to protect participant

confidentiality, because within MTurk it is theoretically possible to determine volunteer

identities via the Amazon online accounts through which they are paid. Within Qualtrics, no

identifying information was recorded, leaving the data set anonymous.

Within Qualtrics, volunteers were first presented with an Informed Consent Screen,

which contained the IRB-approved consent agreement and check boxes for either granting or

declining permission to participate. Volunteers who agreed to take part in the study then clicked

a button to produce the rest of the survey. Otherwise they clicked a decline button and were

prompted to exit from the Qualtrics site.

Those who agreed to participate were randomly assigned to complete either the valence

rating task or the arousal rating task. Prior to beginning the ratings participants were presented

with written instructions indicating that the terms would be presented and rated one at a time and

describing the rating scale. For valence ratings, the anchors ranged from negative emotion to

positive emotion on a scale of 1 = “Unhappy” to 9 = “Happy.” Following the procedure of

Warriner et al. (2013), the current study's instructions explained that “Unhappy” was equivalent

to “annoyed, unsatisfied, melancholic, despaired, or bored,” and “Happy” was equivalent to

“pleased, satisfied, contented, hopeful” (p. 1193; see Appendix B). For arousal ratings, the

anchors ranged from 1 = “Calm” to 9 = “Excited.” Following the procedure of Warriner et al.

19

(2013), the current study's instructions explained that “Calm” was equivalent to “relaxed,

sluggish, dull, sleepy or unaroused” and “Excited” was equivalent to “stimulated, frenzied,

jittery, wide awake, or aroused.”

The data collection session started with nine calibrator words and one attention check

question that asked participants to select a specific number. Attention checks were used in order

to ensure that each participant was attending and understood the instructions. Next, a random list

of ABA terms, general psychological terms, and control words were presented to each

participant. Terms were randomized for each participant. A total of four attention checks were

randomly presented throughout the main task. After participants completed the word-rating task,

they provided demographic information (see Appendix C) and completed the Language Use

subscale of the Acculturation Scale for Hispanics. After the survey was completed, a final screen

thanked the participant and provided a validation code and instructions to return to the MTurk

page to enter the code to receive payment. This screen also included the researchers’ contact

information.

Results

Data Trimming

Several steps were employed to assure that only high-quality data were analyzed.

First, the initial set of nine calibrator words from Warriner et al. (2013) were used to identify

individuals who did not use the rating scale with fidelity (e.g., rating terrorism as happy, or

attack as calm). Next, for each participant, a simple correlation was calculated between

normative ratings from Warriner et al. and those provided by the participant. My original plan

was to eliminate participants with correlation coefficients less than +0.35. After calculating

simple correlations and flagging 111 participants (19/123 from the valence group and 92/114

20

from the arousal group) who produced a correlation of less than +0.35, I decided to use the same

criterion as Warriner et al. (2013), and exclude any participant with a correlation of less than

+0.10.

Using the +.10 cutoff, 11 participants (9%) were eliminated from the valence condition

(instead of 15%), and 38 participants (33%) were eliminated from the arousal condition (instead

of 80%). Because the correlations were so unusual for such a large number of participants in the

arousal condition using the original criterion, the correlation coefficients for control words,

calibrator words, ABA terms, and General Psychological terms were examined separately. For

many participants in the arousal condition, there were very small, or even negative, correlation

coefficients for the ABA and General Psychological terms, but significant positive correlations

for the calibrator and control words. This pattern was not evident for the valence condition and

will be discussed in more detail in the Discussion section below.

Research Questions

Research Question 1 addresses how the emotional valence ratings for ABA technical

terms and General Psychological terms in the current study compare to normative emotional

valence ratings for same-language words generally. Table D-1 shows the percentile bins derived

from Warriner et al.’s corpus of almost 14,000 words, the range of valence ratings that fell in

each of the 10 deciles, and the frequency of ABA terms and General Psychological terms that

fell into each bin. If ABA and General Psychological terms are distributed the same way as

same-language words, generally, we would expect an approximately equal number of words in

each of the 10 decile bins (i.e., approximately 3.6 words per bin for the set of 36 ABA terms).

ABA terms tended to be rated as slightly more unpleasant than same-language words, with 65%

falling below the 50th percentile. Only one of the ABA terms out of 36 fell in the 91-100th

21

percentile bin (the term positive reinforcement) but five of the 36 terms fell in the 0-10th

percentile bin. The 5th column of Tables D-2 and D-3 shows the decile bin corresponding to

each of the ABA and General Psychological terms.

When comparing General Psychological terms to normative emotional ratings for same-

language words generally, these terms were rated as slightly more unpleasant than same-

language-words generally, with 58% falling below the 50th percentile. Additionally, more words

than would be expected based on a uniform distribution were in the extreme deciles. For

example, five out of the 33 General Psychological terms fell in the 91-100th percentile bin and 13

out of the 33 terms fell in the 0-10th percentile bin (i.e., almost 40% of this set of terms were in

the bin corresponding to the lowest possible “unhappy” ratings).

Research Question 2 addresses how the mean emotional response ratings (valence and

arousal) for ABA technical terms compare to the normative emotional response ratings (valence

and arousal) for the same terms in the Warriner et al. (2013) corpus that were analyzed by

Critchfield et al. (2017). To answer the second research question, the mean and standard

deviation of emotional ratings for each term and for each emotion dimension were calculated.

Table D-2 presents the means and standard deviations for all ABA terms used in the current

study with the 13 words used by Critchfield et al. from the Warriner et al. corpus designated with

bold font. For this research question, the focus is on the 13 words used by Critchfield et al. that

were also used in the current study.

Based on the results summarized in Table D-2, I assigned terms to four categories based

on high/low valence x high/low arousal. Following Critchfield et al. (2017), the four categories

were labeled as follows: Blandly Pleasant (Valence M = 5–9 and Arousal M = 1–5), Rousingly

Pleasant (Valence M = 5–9 and Arousal M = 5–9), Blandly Unpleasant (Valence M = 1–5) and

22

Arousal M = 1–5), and Rousingly Unpleasant (Valence M = 1–5 and Arousal M = 5–9).

Critchfield et al. (2017) found that of the 13 ABA terms selected from the Warriner et al. corpus,

seven fell into the “Blandly Pleasant” quadrant, but only four of the words in the current study

did so. Only one of the ABA terms selected by Critchfield et al. fell into the “Rousingly

Pleasant” quadrant, whereas two of the terms in the current study were “Rousingly Pleasant.”

The “Blandly Unpleasant” quadrant had the fewest terms, with one in the Critchfield study and

one in the current study. Lastly, four of the terms selected from the Warriner et al. corpus were

classified as “Rousingly Unpleasant” but six of the terms in the current study were classified as

“Rousingly Unpleasant” (see Figure 1).

Blandly Pleasant (high valence/low arousal)

Rousingly Pleasant (high valence/high arousal)

Warriner et al. Current Study Warriner et al. Current Study Function Escape

Response Behavior Reinforce

Contingency Chain

Function Escape

Response Behavior

Stimulus

Stimulus Reinforce

Blandly Unpleasant (low valence/low arousal)

Rousingly Unpleasant (low valence/high arousal)

Warriner et al. Current Study Warriner et al. Current Study Consequence Contingency Extinction

Deprivation Punishment

Discrimination

Extinction Deprivation Punishment

Discrimination Chain

Consequence Figure 1 Thirteen ABA words with established norms from the Warriner et al. (2013) corpus that were selected for analysis by Critchfield et al. (2017) and rated in the current study and how they were classified. Words that were classified in different categories across the two studies are indicated with italics.

23

The same procedure was followed for the General Psychological terms (see Table D-3 for

means and standard deviations). Of the 26 words for which there are norms from the Warriner et

al. (2017) study, eight terms fell in to the “Blandly Pleasant” category, whereas 10 terms from

the current data set were categorized as Blandly Pleasant. Nine terms fell in to the “Rousingly

Pleasant” category for Warriner et al.’s data, whereas five terms in the current study were

classified as “Rousingly Pleasant.” Two of the selected terms were “Blandly Unpleasant” for

Warriner et al.’s data, but three terms fell in this quadrant in the current study. Finally, seven of

the selected terms were classified as “Rousingly Unpleasant” for Warriner et al.’s data, whereas

eight were classified as “Rousingly Unpleasant” in the current data set (see Figure 2).

Blandly Pleasant (high valence/low arousal)

Rousingly Pleasant (high valence/high arousal)

Warriner et al. Current Study Warriner et al. Current Study Empathy

Plan Feeling

Treatment Therapy Client

Obedience Counseling

Empathy Plan

Feeling Treatment Therapy Client

Confidentiality Referral

Adjustment Mood

Reward Praise

Motivation Incentive Emotion

Confidentiality Referral

Adjustment Mood

Reward Praise

Motivation Incentive Emotion

Blandly Unpleasant (low valence/low arousal)

Rousingly Unpleasant (low valence/high arousal)

Warriner et al. Current Study Warriner et al. Current Study Penalty

Addiction Depression Counseling Obedience

Delusion Denial

Disorder Tantrum Prejudice

Stress Depression

Delusion Denial

Disorder Tantrum Prejudice

Stress Penalty

Addiction Figure 2 General psychological terms (n = 26) with established norms from the Warriner et al. (2013) corpus and the current study and how they were classified. Words that were classified in different categories across the two studies are indicated with italics.

24

Research Question 3 addresses how emotional response ratings (valence and arousal) for

the 36 ABA technical terms compare to the 33 General Psychological terms. Critchfield et al.

used a valence-arousal scatterplot to classify terms from the Warriner et al. corpus. As noted in

Research Question 2, in the current data set the ABA terms and the General Psychological terms

were each categorized into one of the four categories described above (high-valence/low-arousal;

high-valence/high-arousal; low-valence/low-arousal; or low-valence/high-arousal). The ABA

terms that were classified into each of the four categories are presented in Figure 3. The General

Psychological terms are presented in Figure 4.

Blandly Pleasant (high valence/low arousal)

Rousingly Pleasant (high valence/high arousal)

Function Preference Assessment Satiation Shaping Response Behavior

Positive Reinforcement Escape Reinforce Elopement Stimulus Motivating Operation

Blandly Unpleasant (low valence/low arousal)

Rousingly Unpleasant (low valence/high arousal)

Timeout Establishing Operation Operational Definition Token Economy Brief Functional Analysis Antecedent Target Behavior Task Analysis Generalization Differential Reinforcement Reinforcement Schedule Contingency

Discrimination Punishment Deprivation Chain Consequence Extinction Early Intensive Behavioral Intervention Delayed Reinforcement Incompatible Behavior Negative Reinforcement Stereotypy

Figure 3 ABA terms (n = 36) categorized by high and low valence and high and low arousal assigned to each of the four categories of the valence-arousal scatterplot developed by Critchfield et al. (2017).

25

Blandly Pleasant (high valence/low arousal)

Rousingly Pleasant (high valence/low arousal)

Client Therapy Treatment Mood Feeling Adjustment Confidentiality Empathy Referral Plan

Praise Emotion Motivation Incentive Reward

Blandly Unpleasant (low valence/low arousal)

Rousingly Unpleasant (low arousal/high valence)

Depression Play Therapy Counseling Obedience

Disorder Delusion Denial Stress Addiction Chronic Stress Risk Factors Behavior Modification Prejudice Learned Helplessness Substance Abuse Anxiety Penalty Tantrum

Figure 4 General Psychological terms (n = 33) categorized by high and low valence and high and low arousal assigned to each of the four categories of the valence-arousal scatterplot developed by Critchfield et al. (2017).

The percentages of each type of term (ABA, general psychological terms) in each of the

four categories were analyzed with a 2 x 4 Chi-square test of association (see Figure 5). An

association was found between variables, χ2 (3, N=68) = 16.08, p < .001. Thus, in comparing

ABA terms with General Psychological terms, there were differences in the proportion of each

type that were assigned to the four categories. As seen in Figure 5, there were more ABA terms

classified as “blandly unpleasant” relative to the General Psychological terms. Based on the

26

findings of Critchfield et al. (2017), it was expected that for the valence dimension (i.e., pleasant

vs. unpleasant) ABA terms would be rated as more unpleasant than General Psychological terms.

A 2 x 2 Chi-square test of association was used to examine the proportion of ABA and General

Psychological terms classified as pleasant or unpleasant. For the ABA terms, 66% were

unpleasant, while for the General Psychological terms 54% were unpleasant, χ2 (1, N = 68) =

3.00, p = .08. Thus, in the current sample, participants found the two types of jargon equally

unpleasant.

Figure 5 Percentages of ABA technical terms and General Psychological terms that fall into each of the four quadrants of a valence-arousal scatterplot.

0

5

10

15

20

25

30

35

40

45

50

Blandly/Pleasant Rousingly/Pleasant Blandly/Unpleasant

Rousingly/Unpleasant/

Percen

tage)of)terms)in)each)qua

dran

t

ABA/ General/Psychological/

27

The means and standard deviations for the control and the calibrator words for valence

and arousal are presented in Tables D-4 through D-7. These tables also include corresponding

norms from the Warriner et al. (2013) corpus. These data are presented for the sake of

completeness, but as can be seen the means from the current study are very similar to those

found by Warriner et al. (2013), suggesting participants in the current study were appropriately

calibrated.

Study 1 Discussion

The central focus of Study 1 was to replicate and extend previous work on word emotion

by Critchfield et al. (2017) by using a larger set of ABA terms (single words and compound

terms) and presenting these terms to participants to rate rather than using existing word-emotion

corpora. Critchfield et al. (2017) selected 39 words related specifically to ABA from Warriner et

al.’s word corpus along with 35 clinical terms used by ABA practitioners but which are also used

in general clinical practice. They found that ABA terms were rated as more unpleasant than the

clinical terms. In the current study, a set of General Psychological terms was selected for

participants to rate in addition to ABA terms in order to further explore if the effects found by

Critchfield et al. are unique to ABA jargon. In the current study, General Psychological terms

were rated as unpleasant as ABA terms. It is important to note that only three of the general

clinical terms used by Critchfield et al. were used in the current study. The ability to select a

variety of words and compound terms to be presented for novel ratings, rather than using existing

norms, allowed for a novel comparison of emotion ratings between a wider range of ABA and

General Psychological terms. For instance, rather than using existing terms such as “intensive,”

“problem,” and “severe” that may have multiple interpretations, the current study used terms

28

found in psychology textbooks and terms commonly used in therapy such as “substance abuse,”

“risk factors,” and “learned helplessness.”

Consistent with previous research, most individuals found ABA jargon unpleasant. It is

important, however, to note that this effect does not seem to be quite as strong as Critchfield et

al. reported based on word emotion ratings from the Warriner et al. corpus. In other words,

presenting ABA terms and General Psychological terms to participants to rate rather than using

the existing norms produced a different pattern of results. Critchfield et al. (2017) examined

Warriner et al.’s emotional ratings to 34 behavioral assessment words (individual words related

to measuring behavior and detecting clinical effects) and 35 general clinical terms (words that

behavior analysts use but which are not unique to ABA). The terms used in the current study

were generated with the goal of further exploring emotional response ratings to specific ABA

and General Psychological terms.

Each participant in Warriner et al. (2013) rated a set of approximately 350 individual

words from a larger set of nearly 14,000 English words. In the current study, participants rated a

total of 94 terms. About 75% of the items were either ABA technical terms or General

Psychological terms. Although it was not explicitly stated in the instructions that the terms would

be largely focused on behavioral or psychological terms, there is a high likelihood that

participants noticed the pattern. Almost 70% of the participants in both conditions (valence and

arousal) had taken one or more psychology courses. If participants did become aware of this

pattern, it would be difficult to confidently state that the current study is completely “context-

free.” Any differences in ratings for selected terms between the current study and the Warriner et

al. norms may therefore be due to the implicit psychological context provided by the overall set

of terms. This pattern of findings can be explained by the spreading activation mechanism

29

proposed by Anderson (1983). Anderson proposes that concepts in memory are stored in

networks. If one concept is remembered or activated, that activation is quickly spread within

one’s cognitive network such that other related concepts also become remembered at various

levels of activations. For example, when asked to think about the word “lion,” an individual’s

cognitive network will activate related concepts depending on which schema or network

becomes most active. For example, it is possible that “lion” activates concepts such as “tigers”

and “cheetahs” (i.e., those related to big cats), or “zebras” and “elephants” (i.e., related to

African animals). Thus, there is an immediate activation based on previous memories and

experiences that are stored in cognitive networks. In this case, a psychological term such as

“therapist” or “depression” may automatically activate an individual’s conceptual network

related to psychology and the individual might automatically think of related words. If so, ABA

and General Psychology terms that have more than one connotation, such as “discrimination” or

“elopement” would then be interpreted with their psychology connotations rather than the

connotation from the vernacular. When making emotional response ratings to randomly

presented words from the English language, as was the case in Warriner et al., participants may

have encountered words that have both a psychological meaning and a more everyday meaning.

Thus, in this “context-free” setting, it is possible they may have been making emotional

responses to the most dominant meaning of that specific word, which may not be the

psychological meaning.

The results of the cross-study comparison, focused on the 13 ABA terms Critchfield

selected from the Warriner et al. (2013) corpus and the 26 General Psychological words that

have Warriner et al. (2013) norms, show that individuals find General Psychological terms as

unpleasant as ABA terms. After classifying the ABA terms into the four categories (Blandly

30

Pleasant, Rousingly Unpleasant, Blandly Unpleasant, and Rousingly Unpleasant) and comparing

them to Critchfield et al.’s classifications of ABA terms, approximately 40% of the words

switched from the Bland to Rousing categories (i.e., changed in the arousal dimension) in the

current study. There were two exceptions where a word was rated differently on the valence

dimension: “chain” and “consequence.” As previously stated, the context provided in the word

rating task may have contributed to the different pattern of results. For instance, the word

“consequence” may be experienced as a pleasant term within the field of psychology but may

have a less pleasant connotation in the vernacular. Similarly, out of context the word “chain”

may have a neutral connotation (e.g., “bike chain” or “chain mail”) or positive connotation (e.g.,

“necklace”) in the vernacular, depending on which other concepts are activated. In a context that

supports a psychology interpretation, this jargon term seems to have a less pleasant connotation.

As discussed in Chapter II, arousal was measured in Study 1 because it is related to

Skinner’s (1953) description of emotions as motivating operations that make some behaviors

more or less reinforcing to engage in (Critchfield & Doepke, 2018). Additionally, Warriner and

Kuperman (2015) suggested that arousal and valence interact to enhance each other to determine

an overall emotional response to words. After analyzing the data in the current study, however, it

was clear that the correlations were “aberrant” for a large number of participants in the arousal

condition (i.e., 80% of the sample would have been eliminated using the original planned cutoff

criterion). In the arousal condition, there were many non-significant and even negative

correlations between the participant ratings and established norms (Warriner et al., 2013) for the

ABA and General Psychological terms. At the same time, there were significant positive

correlations for these same participants for the calibrator and control words. Such results suggest

that it may have been difficult to decipher and apply the “Calm” to “Excited” anchors and apply

31

them to the ABA and General Psychological terms. Far fewer participants in the valence

condition were eliminated, thus it was easier to apply the “Unhappy” to “Happy” anchors to the

entire set of words. Based on the aforementioned results, the planned arousal ratings were not

included in the methodology for Study 2 because these ratings were potentially neither reliable

nor valid in Study 1./ /

32

CHAPTER IV: STUDY 2

Bilingualism and Word Emotion

Much of the research that has been conducted on emotional responses to specific words

has been conducted with monolingual individuals; however, less is known about how bilinguals

make emotional response ratings to individual words or terms. Previous research on emotional

expression in bilingual individuals has shown that language plays a large role in emotional

expression (Marian & Kaushanskaya, 2008). More specifically, bilingual individuals express

emotions in a different way depending on the language they are using at the time (Marian &

Kaushanskaya, 2008). For example, Anooshian and Hertel (1994) suggested that people use

more emotionally laden terms in their native language than their second language, and that the

native language is what bilingual individuals prefer to use when expressing positive emotions.

According to Bond and Lai (1986) an individual’s second language allows for more distance

from an emotional experience. Marian and Kaushanskaya (2008) suggested that this may be due

to the idea that individuals need to process a second language more deeply, which allows

individuals to build tolerance to the emotions evoked by unpleasant words and encourage further

processing. Such findings are important to consider when working to develop an emotional

connection with bilingual individuals in clinical settings.

There are, however, multiple variables that need to be accounted for in the

aforementioned findings. For instance, previous research on language processing in bilingual

individuals has suggested that cognitive variables such as a bilingual person’s language

proficiency can play a role in overall linguistic processing (Marian & Kaushanskaya, 2008).

Blumenfield and Marian (2007) demonstrated that higher proficiency in a language can lead to

33

more cognitive activation during language processing. Marian and Kaushanskaya (2008)

suggested that rather than proficiency, an important variable to consider is emotional attachment

to the language. That is, although individuals may show competence in a specific language (i.e.,

proficiency), emotional attachment to a language (i.e., preference) may be an indicator of

attachment to the meaning of the language and its associations (Marian & Kaushanskaya, 2008).

Overall, it may be said that although there is a wide agreement that word emotion is an important

component of bilingualism, the existing literature provides no clear basis for predicting specific

word emotion effects in people who speak multiple languages.

Clinical case studies support the possible importance of word emotion in clinical work

with bilingual clients. Specifically, Pavlenko (2008) illustrated how emotional attachment to a

language might be important. These case studies showed that individuals who began therapy in

their second language (English), after refusing to use their native language when given the

option, but then had to switch to their first language experienced either breakthrough or

emotional outbursts when using their native language (Aragno and Shlachet, 1996; Javier, 1995;

Movahedi, 1996). Pavlenko (2008) suggested that this pattern of behavior might be due to the

memories that come with words expressed in the native language. Such results encourage further

research in the area of word emotionality in bilinguals in order to enhance communication

between therapist and clients.

My second study focuses on bilingual (English and Spanish) speakers because past

research suggests that even within the same individual emotional responses are not necessarily

equivalent for “equivalent” translated terms (e.g., Pavlenko, 2008). I asked individuals to rate

terms in both English and Spanish, and I compared these reactions, taking into account each

rater’s level of acculturation, which roughly means degree of comfort in each language. The

34

focus of Study 2 is to address differences and/or similarities in word emotion ratings made by

bilingual speakers and to explore whether language acculturation and language preference for

expressing emotion has an influence on these emotion ratings. Based on the findings described in

Chapter III regarding lack of consistency in arousal ratings, participants were not asked to

complete an arousal rating for the ABA and General Psychological terms in Study 2. The current

study focuses only on emotional ratings of valence.

The specific research questions that addressed in the second study are:

Research Question 4: Are valence ratings for English and Spanish terms positively

correlated when rated by bilingual speakers? Are there specific terms where there are notable

differences between bilingual participants’ ratings in English and Spanish?

Research Question 5: Are the emotional response ratings made by bilingual speakers

to the same terms in English and Spanish related to their preferred language for

communication (English, Spanish, or both equally)?

Research Question 6: Are the emotional response ratings made by bilingual speakers

to the same terms in English and Spanish related to their preferred language for expressing

negative emotions?

Research Question 7: Are the emotional response ratings made by bilingual speakers

to the same terms in English and Spanish related to their preferred language for positive

emotions?

Method

Participants

A total of 141 volunteers who were at least 18 years of age were recruited through

mTurk. Volunteers who completed the survey and responded to attention check questions

35

correctly were paid $1.25 for their participation. Volunteers were bilingual English and Spanish

speakers, and they completed the valence task in both English and Spanish. Participation was

restricted to individuals who reside in the United States and Mexico.

Of the 141 volunteers who completed the survey, 15 were eliminated for one of the

following reasons: (a) responses consisted of clear repeating patterns (e.g., 4, 5, 6, 4, 5, 6, 4, 5,

6…); (b) they did not use the whole scale (e.g., 7, 7, 7, 7…); or (c) there was a consistently large

difference (i.e., 4 to 5 points) between ratings for the same term in English and Spanish when

rating calibrator and control words that have established norms.

Of the remaining 126 participants, 65 were male (48.4%) and 61 were female (51.6%).

The majority of participants identified as being Hispanic/Latino (n = 65, 51.6%), 51 participants

identified as White/Caucasian (40.5%), five participants identified as Multi-Racial/Multi-Ethnic

(4.0%), three participants Black/African American (2.4%), one participant identified as Native

American (.8%), and another participant identified as Asian/Pacific Islander (.8%). Most

participants had a Bachelor’s Degree (n = 59, 46.8%) or Some College (n = 21, 16.7%). The

average age of the participants was 33.53 years (SD = 9.87). The majority of participants did not

have children (n = 79, 62.7%). Twenty-seven participants (21.4%) reported having at least one

family member who had received behavioral (ABA) services in the past. Seven participants

(5.6%) reported having at least one family member who is presently receiving behavioral (ABA)

services.

Measures

Demographic Survey. Three additional questions were added to the demographics

survey used in Study 2. In order to assess language preference, participants were asked to decide

which language they would prefer receiving new information from various sources that use

36

technical language (e.g., teachers, doctors, plumbers). In order to assess emotional attachment to

language, participants were asked what language they tend to utilize to express themselves when

they are feeling happy, and an additional question asked what language they tend to utilize to

express themselves when they are feeling angry. Choices included English, Spanish, and No

Choice (Both Equally).

Acculturation: language use. The Language Use subscale of the Acculturation Scale for

Hispanics (Marin et al., 1987) used in Study 1 to confirm that respondents were monolingual

was used to assess the level of bilingualism for each individual (see Appendix A).

Materials

The same materials used in Study 1 were used. Each word or term was translated into

Spanish for use in the Spanish version of the word-emotion rating task.

Design and Procedure

Bilingual participants were presented with instructions in Spanish. Participants then

completed a calibration task that included terms in both English and Spanish and two attention-

check questions. Participants were then randomly assigned to complete the main task in either

English or Spanish first. The order of language presentation for each of the main rating tasks was

randomized per participant in order to minimize the possibility of sequence effects. Following

the rating tasks, participants completed the demographics questionnaire and acculturation scale

in Spanish.

Results

Language Preference: Descriptive Statistics

Data were collected from two different sources in order to classify participants’ language

preference for communication: The Acculturation Scale for Hispanics (Marin et al., 1987) and

37

the set of three demographics questions directly asking about language choice when (a) receiving

technical information, (b) expressing happiness, and (c) expressing anger. The five questions in

the acculturation scale were summed (range: 5 to 25). The three questions that asked about

language preference were also summed (range: 3 to 9). All individual items were significantly

correlated at p ≤ .001 with r values ranging from .33 to .68. The overall acculturation score and

the overall language preference scores were significantly correlated, r(124) = .66, p ≤ .001

Research Questions

Research Question 4 addresses whether emotional response ratings for English and

Spanish terms correlated when rated by bilingual speakers. Of particular interest was whether

any ABA terms show large differences in emotional response in English and Spanish. In order to

answer this question, mean ratings and standard deviations for each term were derived for each

language (Spanish and English). Means and standard deviations for pairs of terms are presented

in Table D-8 (ABA terms), Table D-9 (General Psychological terms), Table D-10 (Control

words), and Table D-11 (Calibrator words). The fifth column of Tables D-8 through D-11 shows

the correlation between the term in English and in Spanish. Overall, it is notable that most terms

rated in English and Spanish by bilingual individuals were highly correlated.

As reported in Table D-8, emotional valence ratings for 32 out of 36 of the ABA terms in

English and Spanish were significantly correlated (p < .05). For the General Psychology Terms,

29 out of 32 terms were highly correlated (p < .01) and 3 out of 32 were significantly correlated

(p < .05) (see Table D-9). All 13 English and Spanish Control words were highly correlated (p <

.01; see Table D-10). Finally, as can be seen in Table D-11, emotional valence ratings for all

nine Calibrator words in English and Spanish were highly correlated (p < .01). Thus, the current

results suggest that ABA and General Psychological technical jargon had similar emotional

38

response ratings in both English and Spanish when rated by Bilingual speakers.

To explore if there were any ABA terms that showed large differences in emotional

response in English and Spanish, paired-samples t-tests were conducted. As can be seen in Table

D- 8, there were significant differences for the following pairs of ABA terms in English and

Spanish: shaping/moldeamiento; preference assessment/evaluación de preferencias;

elopement/conducta de fuga; generalization/generalización; differential

reinforcement/reforzamiento demorado; time-out/tiempo fuera; incompatible behavior/conducta

incompatible; and deprivation/privación. Given the number of t-tests, however, this finding

should be interpreted with caution (discussed in more detail below).

Research Question 5 addressed whether a bilingual individual’s emotional response

ratings made to the same terms in English and Spanish is related to their preferred language for

communication (English, Spanish, or bilingual) based on their acculturation score. To address

this question, I first computed a difference score between ratings for the same term in Spanish

and English. Difference scores could range from -8 (English has stronger happiness rating) to +8

(Spanish has stronger happiness rating) with a 0 indicating no emotional valence rating

difference between the two languages. Next, correlations between acculturation score and

difference scores were computed. The seventh column in Tables D-8 through D-11 show these

correlations. A positive correlation means that the more strongly Spanish a bilingual person is,

the more the Spanish term was rated higher compared to its English equivalent. Similarly, the

more strongly English a bilingual a person is, the more the English term was rated higher than its

Spanish equivalent. In contrast, a negative correlation indicates that the more strongly Spanish

dominant a bilingual person is, the more the English term was rated higher than Spanish and the

more English a bilingual person is, the more the Spanish term was rated higher than English. As

39

can be seen in Table D-8, there was a significant negative correlation (p < .05) between the

difference score for stimulus/estimulo and acculturation in the ABA word list. Similarly, Table

D-10, shows that there was a significant positive correlation (p < .05) between the difference

score for give/regalar and acculturation score in the Control word list. Overall, however, there

appears to be very little relationship between acculturation score and differences between

English and Spanish ratings of emotional valence by bilingual individuals.

A similar procedure was completed to answer the question related to preferred language

for expressing emotions. For Research Question 6 (angry) the correlations are shown in the

eighth column of Tables D-8 through D-11, and for Research Question 7 (happy) the correlations

are in the 9th column of Tables D-8 though D-11. Column 8 in Table D-8 shows correlations of

difference scores with language preference when angry. For the ABA terms, there were

significant positive correlations (p < .05) between language preference when upset and the

difference scores for positive reinforcement/reforzamiento positivo and reinforcement

schedule/programa de reforzamiento. For the General Psychological word list there were

significant positive correlations (p < .01) between the difference scores for praise/alabanza and

behavior modification/modificación de comportamiento (p < .05) and language preference when

upset, but significant negative correlations between the difference scores for tantrum/berrinche

and play therapy/terapia ludica and language preference when upset. Lastly, there was a

significant positive correlation (p < .05) between the difference score for knowledge/sabiduria

and language preference when upset in the Control word list. There were no significant

correlations between difference scores and language preference when angry in the Calibrator

word list.

40

Finally, the ninth column in Tables D-8 through D-11 shows correlations of difference

scores with language preference when happy. There were no significant correlations between

difference score with language preference when happy in the ABA word list. There was a

significant negative correlation between the difference score for learned helplessness/indefensión

aprendida (p < .01) and the difference score for tantrum/berrinche (p < .05) and language

preference when happy in the General Psychological word list. There was a significant positive

correlation (p < .05) between the difference score for hug/abrazo and language preference when

happy in the Calibrator word list. There were no significant correlations between difference

scores and language preference when happy in the Control word list.

Study 2 Discussion

The focus of Study 2 was to investigate differences and similarities in word emotion

ratings for English terms and their Spanish translations made by bilingual speakers and to

explore whether language acculturation and language preference for expressing emotion is

related to differences in emotion ratings for the two languages.

Emotional response ratings for English and Spanish terms were correlated when rated by

bilingual speakers. The results showed that bilingual individuals tended to rate terms in both

English and Spanish very similarly when rating emotional valence, and this was true for all

categories of terms (i.e., Calibrators, Control, ABA terms, General Psychological terms).

Furthermore, I explored whether there were specific terms where there were notable differences

between bilingual participants’ ratings in English and Spanish. There were significant differences

for 8 of the 36 ABA terms. This finding should be interpreted with caution due to the number of

t-tests conducted. It is also important to note that many of the terms have an additional meaning

in one or both languages. For example, the word “elopement” has an alternate meaning in the

41

English vernacular related to marriage, whereas the translated ABA term in Spanish refers to

“behavior of flight.” However, the terms “generalization” and “generalización” are almost

identical in English and Spanish. It would therefore be pure speculation as to why these were

rated differently in each language by bilingual participants. Other terms, such as “tiempo-fuera”

is a direct translation of the English term “time out.” However, in Latinx American families, the

term “tiempo-fuera” is not very commonly used with children as a consequence. Instead,

children might be accustomed to hearing the word “castigo” (punishment) to communicate that

they are being placed in time-out or will be grounded from reinforcing activities. Furthermore, in

some cases the hybrid term “un time-out” might be used in bilingual contexts such as home or

school. Although there were some notable differences, there is not an obvious single pattern to

explain why these differences might exist.

I also explored whether bilingual speakers’ emotional response ratings for the same

terms in English and Spanish are related to their preferred language for communication. After

computing correlations between acculturation scores and emotional response rating difference

scores (Spanish-English rating), there were very few significant correlations (positive or

negative). This pattern means that there was very little relationship between acculturation score

and differences between English and Spanish ratings of emotional valence by bilingual speakers.

Additionally, emotional ratings in English and Spanish for General Psychological terms were not

related to language dominance in bilingual speakers.

Previous research has suggested that bilingual individuals express emotions in a different

way depending on the language they are using at the time (Marian & Kaushanskaya, 2008). In

Study 2 I explored whether the emotional response ratings made by bilingual speakers to the

same terms in English and Spanish were related to their preferred language for expressing

42

negative (angry) and positive (happiness) emotions. There was a significant positive correlation

between difference scores and language preference when angry for only two terms from the

ABA word list and for four words from the general psychology list (two significant positive

correlations and two significant negative correlations). There were no observed correlations

between difference scores and language preference when expressing happiness in the ABA word

list. Two negative correlations were found between/difference scores and language preference

when happy in the General Psychological word list (“learned helplessness” and “tantrum”).

These results support the idea that while there were some relationships between language

dominance and emotional response to specific words, those relationships were minimal.

Therefore, Bilingual participants rated ABA terms and General Psychological terms as largely

equivalent regardless of language dominance. The implications of these findings for clinical

work with bilingual clients will be discussed in Chapter V.

43

CHAPTER V: CONCLUSION

General Discussion

Applied Behavior Analysis is a well-established, effective, evidence-based approach to

clinical and behavioral practice (e.g., National Autism Center, 2015). The image of applied

behavior analysts among individuals outside the field, however, is not always positive. Bailey

(1991) suggested that ABA has a “marketing problem” (p. 447) because its practitioners and

interventions are viewed as unpleasant or undesirable. Previous research has shown that many

jargon words used in the practice of ABA may elicit unpleasant emotional responses in clients or

parents of child clients. Unpleasant emotional responses have the potential to interfere with

communication between practitioners and clients or may result in clients seeking alternate forms

of treatment.

Critchfield et al. (2017) examined emotional responses to words that can be considered

jargon in science, clinical work, and behavioral assessment. These terms had established

normative ratings reported by Warriner et al. (2013). As the authors predicted, the ABA terms

they selected from the corpus were rated as more unpleasant than other professional terms and

more unpleasant than English words generally (Critchfield et al., 2017). In order to extend this

work, the current study assessed the emotional responses native English speakers and Bilingual

Spanish-English speakers have to ABA and General Psychological jargon.

Through my replication and extension of previous work, I examined how the emotional

response ratings of valence and arousal for ABA technical terms published previously compared

to the novel ratings collected in the current study. After comparing 13 ABA terms that have

44

established norms to ratings made by participants, the results showed that ratings made by

participants in the current study are largely consistent with the norms in the established corpus.

I compared the ratings of 36 ABA terms and 33 General Psychological terms with

English language words in general by constructing10 decile bins for the Warriner et al. corpus of

almost 14,000 words. Many of the ABA terms in the current study appeared to be rated as more

pleasant than ratings from previous word emotion rating work. However, it is important to

highlight that on a nine-point rating scale, the highest rated ABA term (positive reinforcement)

was rated at a 7.25. The remainder of the terms that were rated above the mid-point on the

pleasantness dimension had a mean valence of 5.0, indicating that even though they were

classified in the “high valence” category they were at the lower end of the category cutoff.

Additionally, General Psychological terms were found to be experienced as unpleasant, if not

more unpleasant, than ABA terms. As previously stated, about 70% of the participants in both

conditions had taken one or more psychology courses. It is possible that this contrasting finding

could be due to the context that was set up in the current study by asking individuals to rate 71

terms related to psychology out of 94 total words. Note also that several of the Control and

Calibrator words could be considered peripherally related to psychological concepts (e.g., smile,

relax, dream, knowledgeable, sex, suicide, hug, laughter). Therefore, it may have been difficult

for participants to distinguish between ABA technical terms and General Psychological terms

used in practice as explained by the spreading activation mechanism proposed by Anderson

(1983) and described in Chapter IV.

My second study focused on bilingual (English and Spanish) speakers because past

research suggests that even within the same individual, emotional responses are not necessarily

equivalent for “equivalent” translated terms (e.g., Pavlenko, 2008). I asked Bilingual individuals

45

to rate terms in both English and Spanish on the valence dimension (“Unhappy” to “Happy” and

“Infeliz” to “Feliz”). Because of challenges faced by participants with the arousal dimension in

Study 1, the ratings of “Calm” to “Excited” were not collected in Study 2.

I compared emotional ratings made in English and Spanish taking into account each

rater’s level of acculturation, which roughly corresponds to degree of comfort in each language.

Study 2 focused on addressing differences and similarities in word emotion ratings made by

bilingual speakers and to explore whether language acculturation and language preference for

expressing emotion had an influence on these emotion ratings. The results of the current study

show that bilingual individuals rated terms in both English and Spanish very similarly when

rating the emotional valence of the words in all four categories: Calibrator words, Control words,

ABA terms, and General Psychological terms. It is possible that Bilingual individuals who are

heavily immersed in both the English and Spanish languages understand the meaning of the same

word (e.g., “consequence” vs. “consecuencia”) as having similar emotional connotations.

Study 2 also assessed whether there were specific terms where there were notable

differences between bilingual participants’ ratings in English and Spanish. Although there were 8

out of 36 ABA terms with significant differences, this finding should be interpreted with caution

due to the number of t-tests conducted. For 36 t-tests, it was expected that a handful of terms

would be significant due to chance itself (i.e., about 5% or 2 of 36). Using an adjusted alpha

level to account for the multiple tests (e.g., using .05/36 = .001), only 3 of the differences would

be considered statistically significant. Given the expectation of this many significant findings

due to chance alone, the differences should not be over-interpreted.

Another important note, however, is the fact that many of the terms have additional

meanings in one of the two languages. Individuals may have had a different emotional response

46

to a specific word based on the meaning the word has in the vernacular rather than the meaning

the word has within the field of ABA (e.g., discrimination). While there were some differences,

there was no specific, obvious pattern for the set of words rated differently in English and

Spanish, and it is difficult to explain why these particular terms were rated differently in the two

languages. Overall, the conclusion from the pattern of findings is that emotional valence ratings

for English ABA terms and their Spanish translations are correlated. This same conclusion can

be drawn for English psychological terms and their Spanish translations.

The current study also explored whether a Bilingual individual’s emotional response

ratings for the same terms in English and Spanish is related to their preferred language for

communication (English, Spanish, or bilingual). The results suggested that there is a small

relationship between acculturation and differences between English and Spanish ratings of

emotional valence by Bilingual speakers. Similarly, there were very few significant correlations

when assessing whether the emotional response ratings made by Bilingual speakers to the same

term in both languages were related to their preferred language for expressing negative (angry)

and positive (happy) emotions. Overall, the answer to these research questions is that due to the

high correlations between English and Spanish terms, there appears to be little relationship

between differences in English and Spanish terms and the measures of language preference in

Bilinguals. It is possible that because both English and Spanish derive from Latin, the cognates

present (e.g., generalization vs. generalización) add to the lack of differences in ratings found

between words. Furthermore, the Bilingual sample in this study identified as highly proficient in

both languages. As such, it is possible that the connotation of words in both languages evoke

similar emotional responses.

47

Strengths and Limitations of the Current Study

One strength of the current study was that it examined novel emotional ratings from a

novel sample of participants. Previous studies have assessed the emotional response ratings to

various ABA and General Psychological terms. However, these assessments have been

conducted through examinations of word emotion ratings of these words established in published

norms (e.g., Warriner et al., 2013). Obtaining novel ratings from a large sample of individuals

from the general population is beneficial because it allows us to draw conclusions about the

emotional responses individuals have to technical jargon in the context of other jargon terms.

Furthermore, the ability to obtain novel ratings of ABA and General Psychological terms

allowed for the introduction of a new range of terms that were more representative of technical

language by being able to obtain ratings for compound terms (e.g., “positive reinforcement”,

“early intensive behavioral intervention”) commonly used in clinical and therapeutic settings.

Another strength of this study was in the examination of emotional responses to technical

jargon by English-Spanish bilingual individuals. Critchfield and Doepke (2018) found that

behavior analysis terms elicit negative emotions in five languages. However, their results were

limited by the available norms in the existing language corpora, and their examination focused

on monolingual speakers, rather than Bilingual speakers. Based on the effects that have been

found in previous research, it was important to examine the emotional responses Bilingual

individuals have to jargon in both languages, particularly with respect to the fact that the answer

to this research question has potential implications for treatment delivery. Prior to the current

study, it was unclear how bilingual individuals would react to technical jargon in both languages.

As noted in Chapter II, Pavlenko (2008) suggested that emotional attachment to a language

might be important. Therefore, being Bilingual may mean that one has a different level of

48

emotional attachment to one language as opposed to the other. However, in the current study,

any potential effect of language attachment was not overly evident. Although the results of the

current study show that bilingual individuals have similar emotional responses to technical terms

in both languages, it is important for practitioners to be aware of the results of the current study

when working with individuals who identify as Bilingual. That is, there may be no specific

advantage to conduct therapy sessions in one language over the others for those who are fluently

bilingual. The same cautions for using technical jargon apply regardless of language.

One limitation of the current study is that words were presented to individuals one at a

time without additional context. It is therefore difficult to assume that participants knew the

meaning of each of the words/terms presented. The lack of context for words that have more than

one meaning (e.g., “chain” or “extinction”) means that alternate interpretations for those ratings

are possible. Similarly, there may have been words for which some participants may have been

unclear about the meaning. Although 70% of the participants had taken at least one psychology

course, 30% of the participants may not have been familiar with all of the terms (e.g., “learned

helplessness” or “stereotypy”). The lack of a meaning for some terms may have caused

individuals to have a different emotional response than they would have if they clearly knew the

meaning of each term or were able to derive meaning from context.

Another limitation of the present investigation is that I was unable to recruit a large

sample of monolingual native Spanish speakers to complete the word-rating task. Previous

research by Critchfield and Doepke (2018) found that native Spanish speakers rated ABA

technical jargon just as unpleasant as native English speakers, although they were limited to

using existing published norms as well. Given that the current study added and examined new

49

compound ABA terms and General Psychological terms, it would have been beneficial to

examine data from monolingual Spanish speakers as well.

A limitation related to the emotional dimensions measured was that the arousal ratings

that were measured in Study 1 were not included in Study 2. Arousal ratings were an area of

interest because they are related to Skinner’s (1953) description of emotions as motivating

operations that make some behaviors more or less reinforcing to engage in (Critchfield &

Doepke, 2018). After analyzing the data from Study 1, however, the correlations between

participant ratings and established norms were non-significant or negative for the majority of

participants in the arousal condition. Participants clearly found it difficult to apply the “Calm” to

“Excited” anchors to the ABA and General Psychological terms while at the same time they were

making ratings consistent with those of established norms for the Control and Calibrator words.

It was assumed that the same difficulty would apply to the task when conducted in Spanish using

the “Tranquilo/Tranquila” and “Exitado/Exitada” anchors. Therefore, I did not examine arousal

ratings for bilingual participants.

Lastly, another limitation of the current study was that the measures utilized in Study 2

assessed language preference when expressing oneself, but the rating task the participants

completed in the current study focused on receptive language. For instance, the Language Use

subscale of the Acculturation Scale asked participant to answer questions related to language

spoken at home, language spoken as a child, and language spoken with friends. Similarly, the

language preference questions asked participants to answer questions related to language

preference when expressing happiness and anger. It would therefore be beneficial to include

measures that assess receptive language to match the rating scale used in the current study.

50

Directions for Future Research

Based on the various limitations in the current study, there are many potential directions

for future research on emotional responses to ABA and psychological jargon. Researchers are

encouraged to find a large representative sample of native Spanish speakers. As the word rating

procedure is relatively simple to use, it would be feasible to appropriately translate the task to

meet the needs of the native Spanish speaking population. With the growing population of the

Latinx community in the United States, it is important to ensure that we find the best language to

communicate with this population in therapy settings.

Future researchers should find an alternate way to present the arousal dimension to study

emotional responses to technical jargon terms. The results of the current study showed that the

inconsistent arousal ratings may have been due to the confusion caused by the anchors “Calm” to

“Excited.” This confusion was not evident for the ratings made to calibrator and control words

such as “party” or “meditation” and so there was something about asking participants to apply

these terms to psychological and ABA jargon that they found difficult or unclear. Future

research might assess and apply more appropriate anchor descriptors to ensure that the

measurement of the “arousal” dimension. Perhaps the anchors “Not Motivating” to “Motivating”

might be easier for subjects to use and apply in a rating task. In order to address how arousal and

valence interact to influence an overall emotional response to words or terms, it is important to

have a reliable and valid method of assessing word emotion arousal.

Another consideration for future research is developing an assessment method whereby

technical terms can be studied in a more meaningful context. Although the current study may

have provided context in the form of asking participants to rate a large number of terms

pertaining to the field of psychology, context could be specifically provided by asking

51

participants to rate terms they read about in vignettes describing intake or therapy sessions. This

procedure would enable comparisons to simple-language equivalents. For instance, participants

could read a vignette describing an ABA treatment to a parent using technical jargon (e.g.,

“reinforce”) and read another vignette using simple language (e.g., “praise” or “reward”). Such

comparisons could produce findings that would allow practitioners to consider alternate methods

of communication about ABA concepts with individuals in clinical and applied settings.

An important consideration for the current research is the relationship between culture

and language. As Jiang (2000) stated, language is an important part of culture. Jian described

language as a component that defines culture but that is also influenced and shaped by it.

Although the results of the current study suggest that technical language has unpleasant

overtones in both English and Spanish, it would be important to delve into the differences within

the Bilingual individuals’ various cultures. Even though it can be difficult to define what it truly

means to be Bilingual, the responses between a Bilingual individual who identifies as Latinx and

a Bilingual individual who identifies as White could have a large impact in the emotional

responses to specific terms based on their different cultural backgrounds. It is therefore important

for future research to consider the relationship between culture and language and assess these

differences when studying the emotional impact of jargon.

Clinical Implications!

There has been a growing concern that the vocabulary used by practitioners in the field of

ABA causes distance between the individual practitioners who deliver ABA services and the

clients who are searching for behavioral services. As Critchfield et al. (2017) emphasized, the

vocabulary of behavior analysis has remained consistent since it was first developed from the

1930s to the 1950s. It is important to recognize, however, that the client base in need of support

52

from the field of ABA is continually changing and growing. A major focus of the field is the

dissemination and application of theories (Baer et al., 1968), and it is the field’s ethical

responsibility to adhere to the commitment to the clients who need support.

Based on the results from previous research and the current study, it is important to

recognize that ABA technical language and General Psychological technical language can elicit

unpleasant emotional responses. In addition, the current study adds the finding that Bilingual

Spanish and English speakers have a similar unpleasant emotional response to technical terms in

both languages. It is therefore important for the field to begin seeking new terms that evoke more

positive emotional responses to improve communication and rapport between clients and

therapists.

The results of the current study could also be used to encourage practitioners to reflect on

the impact of mental health related stigma. Although there is an understanding that mental health

support can and should be positive, there may still be an unconscious stigma associated with the

field in general. The finding that behavioral and psychological terms that are experienced as

unpleasant may be related to the fact that individuals often avoid or delay seeking mental health

support due to the stigma and/or embarrassment associated with it. For instance, Clement et al.

(2015) conducted a meta-analysis that suggested that stigma has a clear effect, albeit small to

moderate sized, for seeking mental health support and there is a need for new interventions that

can help minimize the effect of perceived stigma. Clement et al. suggested that one method to

decrease mental health stigma is through by reaching out to the community and providing

psycho-education about the field of mental health and the services available to potential clients.

Although this suggestion may be a great opportunity for mental health professionals to help

decrease the stigma associated with mental illness and treatment, it is important to consider the

53

emotional valence associated with terms related to mental health or psychological jargon before

providing such psycho-education. If this factor is not considered, then providing psycho-

education with jargon may cause more damage and continue increasing the gap between

therapists and individuals who are in need of mental health services.

Furthermore, with the growing Bilingual population, it is important to find the best

methods to increase communication in various languages. As noted in Chapter II, the ABA

community has produced glossaries of technical terms in several languages, including Spanish

(https://www.bacb.com/wp-content/uploads/2017/09/ Spanish-English-ABA-Glossary.pdf).

However, there has been minimal research on how individuals outside the field of ABA actually

understand or experience these terms. Many of these terms have been literally translated, which

means that individuals in the Latinx community may have a difficult time understanding the

meaning of these translated words, even if the argument is that the words are in their native

language. Additionally, many translators who are hired from various agencies may not have the

background to understand and explain to a client that the word “discrimination” for example,

does not have the same meaning in the field of ABA as it does in the vernacular. Therefore,

using literal translations may cause more harm in a therapeutic relationship. A similar problem

may arise when therapists who are native English speakers try to use the glossary to

communicate using some Spanish for their clients. While therapists in this situation are trying to

enhance communication with their clients, using literal translations may also cause significant

harm and impair communication.

Overall, jargon can be an efficient and effective way to communicate within a community

of professionals within the same field. However, when communicating with members outside the

field, as when communicating with a client, a parent of a client, or a teacher of a client, there is a

54

potential for damage to the therapeutic relationship based on the language used to communicate.

It is therefore important to continue exploring various methods to decrease the potential to

transmit unintended emotional baggage and increase the accuracy and ease of communication

between client and therapist.

55

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61

APPENDIX A: SHORT ACCULTURATION SCALE

English Version

1.! In general, what language(s) do you read and speak? 1

Only Spanish

2

Spanish better

than English

3

Both Equally

4

English better

than Spanish

5

Only

English

2.! What was the language(s) you used as a child? 1

Only Spanish

2

Spanish better

than English

3

Both Equally

4

English better

than Spanish

5

Only

English

3.! What language(s) do you usually speak at home? 1

Only Spanish

2

Spanish better

than English

3

Both Equally

4

English better

than Spanish

5

Only

English

4.! In which language(s) do you usually think? 1

Only Spanish

2

Spanish better

than English

3

Both Equally

4

English better

than Spanish

5

Only

English

5.! What language(s) do you usually speak with your friends? 1

Only Spanish

2

Spanish better

than English

3

Both Equally

4

English better

than Spanish

5

Only

English

Spanish Version

62

1.! Por lo general, qué idioma(s) leé y habla usted? 1

Solo Español

2

Español mejor

que Inglés

3

Ambos por igual

4

Inglés mejor que

Español

5

Solo Inglés

2.! Cual fué el idoma(s) que habló cuando era niño(a)? 1

Solo Español

2

Español mejor

que Inglés

3

Ambos por igual

4

Inglés mejor que

Español

5

Solo Inglés

3.! Por lo general, en qué idioma(s) habla en su casa? 1

Solo Español

2

Español mejor

que Inglés

3

Ambos por igual

4

Inglés mejor que

Español

5

Solo Inglés

4.! Por lo general, en qué idioma(s) piensa? 1

Solo Español

2

Español mejor

que Inglés

3

Ambos por igual

4

Inglés mejor que

Español

5

Solo Inglés

5.! Por lo general en qué idioma(s) habla con sus amigos(as)? 1

Solo Español

2

Español mejor

que Inglés

3

Ambos por igual

4

Inglés mejor que

Español

5

Solo Inglés

63

APPENDIX B: INSTRUCTIONS FOR WORD RATING TASK

Adapted from Warriner et al. (2013)

Valence Instructions

You are invited to take part in the study that is investigating emotion, and concerns how people

respond to different types of words. You will use a scale to rate how you felt while reading each

word.

There will be approximately 90 words. To rate each word, you will use a scale that range from 1

(unhappy) to 9 (happy).

At one extreme of this scale, you feel completely unhappy, annoyed, unsatisfied, melancholic,

despaired, or bored. You can indicate feeling completely unhappy by selecting 1.

The other end of the scale is when you feel completely happy, pleased, satisfied, contented, or

hopeful. When you feel completely happy you should indicate this by choosing rating 9.

The numbers also allow you to describe intermediate feelings by selecting other values (e.g., 2,

3, 4 or 6, 7, 8). If you feel completely neutral (neither happy nor unhappy), then select the middle

of the scale (rating 5).

Please work at a rapid pace and don’t spend too much time thinking about each word. Rather,

make your ratings based on your first and immediate reaction as you read each word.

Arousal Instructions

You are invited to take part in the study that is investigating emotion, and concerns how people

respond to different types of words. You will use a scale to rate how you felt while reading each

64

word.

There will be approximately 90 words. To rate each word, you will use a scale that range from 1

(calm) to 9 (excited).

At one extreme of this scale, you feel completely relaxed, calm, sluggish, dull, sleepy, or

unaroused. When you feel completely calm you should indicate this by choosing rating 1.

The other end of the scale is when you are stimulated, excited, frenzied, jittery, wide-awake, or

aroused. You can indicate feeling completely aroused by selecting 9.

The numbers also allow you to describe intermediate feelings of calmness/arousal by selecting

other values (e.g., 2, 3, 4 or 6, 7, 8). If you feel completely neutral (neither excited nor calm),

then select the middle of the scale (rating 5).

Please work at a rapid pace and don’t spend too much time thinking about each word. Rather,

make your ratings based on your first and immediate reaction as you read each word.

65

APPENDIX C: DEMOGRAPHICS

Demographic Information (English Version)

Age: _____________

Gender Identity (circle): Male Female

Other (e.g. transgender, gender queer), please specify: _______________

Marital Status: Single_______ Married______ Widowed________

Racial/Ethnic Identity: ____White/Caucasian

____Black/African American ____Hispanic/Latino ____Asian/Pacific Islander ____Native American ____Multi-Racial/Multi-Ethnic ____Other (Please Specify):____________ Country of Origin: _____________________ Country of Residence: _______________________

Years of Education: _____

1 = some high school 5 = Bachelor’s degree

2 = high school 6 = some postgraduate study

3 = some college 7 = Master’s degree

4 = Associate’s degree 8 = Doctorate or professional degree

List the number of psychology courses taken at the college level?

66

What is your father’s highest level of education? ____________

What is your mother’s highest level of education? _____________

1 = some high school 5 = Bachelor’s degree

2 = high school 6 = some postgraduate study

3 = some college 7 = Master’s degree

4 = Associate’s degree 8 = Doctorate or professional degree

In what social class would you place your family as you were growing up? ___________

1 = lower class 4 = middle class

2 = working class 5 = upper middle class

3 = lower middle class 6 = upper class

7 = Prefer not to answer

Do you have any children?

_____Yes

_____No

Do you and/or anyone in your direct family have any other serious physical, intellectual, or

developmental disabilities or mental illnesses?

____ Yes

____No

67

Have you and/or anyone in your direct family received behavioral services in the past?

____Yes

____No

Are you and/or anyone in your direct family currently receiving behavioral services?

____Yes

____No

Additional Questions for Study 2 Participants

In which language are you more comfortable receiving new information?

For example, when you receive specialized or technical information from various kinds of

experts in health fields (such as doctors, dentists, therapists, counselors, etc.) and other

specializations (e.g., accountant, lawyer, car mechanic, plumber, electrician, etc.), would you

rather have discussions in English, Spanish, or both/either?

English Spanish No Choice (both equally)

In times when you are very angry, what language do you tend to utilize?

English Spanish No Choice (both equally)

In times when you are very happy, what language do you tend to utilize?

English Spanish No Choice (both equally)

68

APPENDIX D: TABLES

Table D-1

Percentile Bins and Valence Rating Cut-offs for the Warriner et al. Corpus and the Distribution of ABA and General Psychological Terms from the Current Study Percentile Bin Valence rating range ABA Terms (36) General Psychological

Terms (33) 0-10th

0 - 3.20 5 13

11-20th

3.21 - 3.94 4 1

21-30th

3.95 – 4.50 4 1

31-40th

4.51 - 4.89 7 1

41-50th

4.90 – 5.20 3 3

51-60th

5.21 – 5.47 4 3

61-70th

5.48 – 5.76 4 3

71-80th

5.77 – 6.14 4 2

81-90th

6.15 – 6.50 0 1

91-100th

6.51 – 9 1 5

69

Table D-2 Descriptive Statistics for ABA Terms in Study 1 ABA Term M SD n Percentile

Bin Category Warriner Norms

Positive Reinforcement Valence Arousal

7.25 5.16

1.30 2.36

112 76

91-99th

Rousingly Pleasant

N/A N/A

Satiation Valence Arousal

5.91 3.97

1.72 1.93

112 76

71-80th

Blandly Pleasant

N/A N/A

Stimulus Valence Arousal

5.82 7.01

1.43 1.82

112 76

71-80th

Rousingly Pleasant (�)

5.63 (2.01) 4.7 (2.69)

Elopement Valence Arousal

5.79 5.91

1.32 1.50

112 76

71-80th

Rousingly Pleasant

N/A N/A

Function Valence Arousal

5.77 4.24

1.32 1.38

112 76

71-80th

Blandly Pleasant (�)

5.55 (0.76) 4.1 (1.7)

Motivating Operation Valence Arousal

5.59 5.29

1.53 1.68

112 76

61-70th

Rousingly Pleasant

N/A N/A

table continues

70

ABA Term M SD n Percentile Bin

Category Warriner Norms

Incompatible Behavior Valence Arousal

5.58 2.80

1.61 1.37

112 76

61-70th

Rousingly Pleasant

N/A N/A

Response Valence Arousal

5.57 4.57

1.52 1.72

112 76

61-70th

Blandly Pleasant (�)

5.95 (1.5) 3.56 (2.2)

Reinforce Valence Arousal

5.53 5.21

1.32 1.51

112 76

61-70th

Rousingly Pleasant (�)

5.53 (1.5) Blandly pleasant 3.96 (2.33)

Escape Valence Arousal

5.42 6.63

2.13 1.92

112 76

51-60th

Rousingly Pleasant (�)

5.50 (1.76) 4.55 (2.58)

Establishing Operation Valence Arousal

5.35 4.66

1.21 1.50

112 76

51-60th

Blandly Unpleasant

N/A N/A

Shaping Valence Arousal

5.29 4.34

1.26 1.50

112 76

51-60th

Blandly Pleasant

N/A N/A

Behavior Valence Arousal

5.26 4.82

1.15 1.14

112 76

51-60th

Blandly Pleasant (�)

5.28 (1.71) 4.27 (2.16)

table continues

71

ABA Term

M

SD

n

Percentile Bin

Category

Warriner Norms

Preference Assessment Valence Arousal

5.07 4.46

1.55 1.26

112 76

41-50th

Blandly Pleasant

N/A N/A

Contingency Valence Arousal

4.91 4.46

1.15 1.54

112 76

41-50th

Blandly Unpleasant (✔)

4.67 (1.68) 3.22 (2.39)

Operational Definition Valence Arousal

4.89 4.22

1.11 1.55

112 76

31-40th

Blandly Unpleasant

N/A N/A

Token Economy Valence Arousal

4.85 4.39

1.34 1.53

112 76

31-40th

Blandly Unpleasant

N/A N/A

Brief FA Valence Arousal

4.81 4.25

1.35 1.42

112 76

31-40th

Blandly Unpleasant

N/A N/A

Antecedent Valence Arousal

4.79 4.36

1.04 1.55

112 76

31-40th

Blandly Unpleasant

N/A N/A

Target Behavior Valence Arousal

4.72 4.95

1.33 1.63

112 76

31-40th

Blandly Unpleasant

N/A N/A

table continues

72

ABA Term

M

SD

n

Percentile Bin

Category

Warriner Norms

Task Analysis Valence Arousal

4.64 4.32

1.32 1.57

112 76

31-40th

Blandly Unpleasant

N/A N/A

Generalization Valence Arousal

4.51 4.42

1.32 1.50

112 76

31-40th

Blandly Unpleasant

N/A N/A

Differential Reinforcement Valence Arousal

4.48 4.86

1.39 1.57

112 76

21-30th

Blandly Unpleasant

N/A N/A

Reinforcement Schedule Valence Arousal

4.46 4.83

1.35 1.47

112 76

21-30th

Blandly Unpleasant

N/A N/A

Chain Valence Arousal

4.37 1.46

4.70 1.55

112 76

21-30th

Rousingly Unpleasant (✗)

4.79 (1.55) Blandly Pleasant 4.05 (2.33)

Early Intensive BI Valence Arousal

4.19 5.61

1.71 1.80

112 76

21-30th

Rousingly Unpleasant

N/A N/A

table continues

73

ABA Term

M

SD

n

Percentile Bin

Category

Warriner Norms

Delayed Reinforcement Valence Arousal

3.88 4.61

1.43 1.37

112 76

11-20th

Rousingly Unpleasant

N/A N/A

Consequence Valence Arousal

3.49 5.88

1.64 1.53

112 76

11-20th

Rousingly Unpleasant (✗)

3.86 (1.55) Blandly Unpleasant 4.31 (2.09)

Time-out Valence Arousal

3.43 4.21

1.63 1.82

112 76

11-20th

Blandly Unpleasant

N/A N/A

Stereotypy Valence Arousal

3.28 5.13

1.54 1.56

112 76

11-20th

Rousingly Unpleasant

N/A N/A

Negative Reinforcement Valence Arousal

2.28 6.11

1.40 1.67

112 76

0-10th

Rousingly Unpleasant

N/A N/A

Extinction Valence Arousal

2.01 6.41

1.43 3.31

112 76

0-10th

Rousingly Unpleasant (✔)

3.1 (2.34) 5.0 (2.43)

table continues

74

ABA Term

M

SD

n

Percentile Bin

Category

Warriner Norms

Deprivation Valence Arousal

2.00 5.83

1.16 1.84

112 76

0-10th

Rousingly Unpleasant (✔)

2.58 (1.50) 4.57 (1.91)

Punishment Valence Arousal

1.82 7.13

1.16 1.22

112 76

0-10th

Rousingly Unpleasant (✔)

2.76 (1.74) 5.07 (2.51)

Discrimination Valence Arousal

1.76 6.74

1.13 1.54

112 76

0-10th

Rousingly Unpleasant (✔)

2.45 (1.43) 5.62 (2.55)

Note. Items in bold are the terms that have existing Warriner et al. (2013) norms. A ✔ indicates that the term falls in the same category as Warriner et al. An �indicates that the term falls into a different category than Warriner et al. Percentile bins were derived from the Warriner et al. corpus of almost 14,000 words. See text for further explication.

75

Table D-3

Descriptive Statistics for the General Psychological Terms in Study 1

General Psychological Term

M SD n Percentile Bin Category Warriner Norms

Reward Valence Arousal

8.04 6.67

1.09 1.94

112 76

91-100th

Rousingly Pleasant (✔)

7.47 (1.35) 5.58 (2.74)

Praise Valence Arousal

7.80 5.80

1.26 2.19

112 76

91-100th

Rousingly Pleasant (✔)

7.65 (1.31) 5.45 (2.04)

Motivation Valence Arousal

7.21 6.45

1.40 1.81

112 76

91-100th

Rousingly Pleasant (✔)

6.24 (2.05) 4.73 (2.6)

Incentive Valence Arousal

6.99 6.14

1.33 1.72

112 76

91-100th

Rousingly Pleasant (✔)

7.05 (1.47) 4.61 (2.71)

Empathy Valence Arousal

6.72 2.68

1.87 1.84

112 76

91-100th

Blandly Pleasant (✔)

7.29 (1.94) 3.62 (2.06)

Plan Valence Arousal

6.18 3.74

1.21 1.76

112 76

81-90th

Blandly Pleasant (✔)

6.14 (1.46) 3.86 (2.26)

table continues

76

General Psychological Term

M SD n Percentile Bin Category Warriner Norms

Feeling Valence Arousal

6.09 4.38

1.44 1.93

112 76

71-80th

Blandly Pleasant (✔)

6.50 (1.95) 3.86 (2.57)

Emotion Valence Arousal

5.89 5.18

1.55 1.87

112 76

71-80th

Rousingly Pleasant (✔)

6.62 (1.88) 4.75 (2.79)

Play Therapy Valence Arousal

5.71 4.75

1.71 2.19

112 76

61-70th

Blandly Pleasant

N/A N/A

Confidentiality Valence Arousal

5.66 3.92

1.52 1.63

112 76

61-70th

Blandly Pleasant (✗)

5.82 (1.94) Rousingly Pleasant 4.64 (2.38)

Treatment Valence Arousal

5.58 4.09

1.64 1.74

112 76

61-70th

Blandly Pleasant (✔)

5.00 (1.80) 4.47 (2.01)

Referral Valence Arousal

5.44 4.13

1.23 1.46

112 76

51-60th

Blandly Pleasant (✗)

5.52 (1.40) Rousingly Pleasant 4.52 (1.94)

Adjustment Valence Arousal

5.33 4.36

1.26 1.61

112 76

51-60th

Blandly Pleasant (✗)

5.53 (1.22) Rousingly Pleasant 4.59 (2.36)

table continues

77

General Psychological Term

M SD n Percentile Bin Category Warriner Norms

Client Valence Arousal

5.32 4.05

.98 1.51

112 76

51-60th

Blandly Pleasant (✔)

5.22 (1.59) 2.95 (1.99)

Therapy Valence Arousal

5.10 1.82

1.79 1.82

112 76

41-50th

Blandly Pleasant (✔)

5.10 (2.10) 3.74 (1.89)

Mood Valence Arousal

4.97 3.86

1.27 1.72

112 76

41-50th

Blandly Pleasant (✗)

5.29 (1.74) Rousingly Pleasant 4.50 (2.63)

Counseling Valence Arousal

4.96 3.42

1.77 1.58

112 76

41-50th

Blandly Unpleasant (✔)

5.90 (2.13) 3.40 (2.28)

Obedience Valence Arousal

4.86 3.86

1.92 1.67

112 76

31-40th

Blandly Unpleasant (✔)

4.63 (2.09) 3.29 (2.12)

Behavior Modification Valence Arousal

4.13 5.22

1.71 1.53

112 76

21-30th

Rousingly Unpleasant

N/A N/A

Risk Factors Valence Arousal

3.65 6.58

1.55 1.30

112 76

11-20th

Rousingly Unpleasant

N/A N/A

table continues

78

General Psychological Term

M SD n Percentile Bin Category Warriner Norms

Learned Helplessness Valence Arousal

2.89 4.64

1.93 1.76

112 76

0-10th

Rousingly Unpleasant

N/A N/A

Delusion Valence Arousal

2.49 5.54

1.33 1.65

112 76

0-10th

Rousingly Unpleasant (✔)

3.30 (1.84) 4.60 (2.19)

Denial Valence Arousal

2.41 5.30

1.28 1.67

112 76

0-10th

Rousingly Unpleasant (✔)

3.57 (1.78) 4.85 (2.46)

Disorder Valence Arousal

2.36 6.51

1.34 1.61

112 76

0-10th

Rousingly Unpleasant (✔)

3.76 (1.84) 4.90 (2.38)

Penalty Valence Arousal

2.29 6.47

1.29 1.60

112 76

0-10th

Rousingly Unpleasant (✗)

2.80 (1.60) Blandly Unpleasant 3.89 (2.45)

Tantrum Valence Arousal

2.07 7.64

1.33 1.32

112 76

0-10th

Rousingly Unpleasant (✔)

3.15 (1.87) 5.05 (2.36)

Prejudice Valence Arousal

2.04 6.41

1.30 1.45

112 76

0-10th

Rousingly Unpleasant (✔)

2.71 (1.95) 5.35 (2.08)

table continues

79

General Psychological Term

M SD n Percentile Bin Category Warriner Norms

Chronic Stress Valence Arousal

1.98 6.91

1.27 1.30

112 76

0-10th

Rousingly Unpleasant

N/A N/A

Substance Abuse Valence Arousal

1.91 6.64

1.50 1.42

112 76

0-10th

Rousingly Unpleasant

N/A N/A

Addiction Valence Arousal

1.90 6.54

1.47 1.44

112 76

0-10th

Rousingly Unpleasant (✗)

3.52 (1.81) Blandly Unpleasant 4.48 (2.87)

Stress Valence Arousal

1.84 7.68

1.15 1.31

112 76

0-10th

Rousingly Unpleasant (✔)

1.79 (0.92) 4.72 (2.95)

Anxiety Valence Arousal

1.78 7.95

1.11 1.67

112 76

0-10th

Rousingly Unpleasant

N/A N/A

Depression Valence Arousal

1.33 4.04

.73 2.02

112 76

0-10th

Blandly Unpleasant (✗)

2.44 (1.87) Rousingly Unpleasant 5.2 (2.09)

Note. Items in bold are the terms that have existing Warriner et al. (2013) norms. A ✔ indicates that the term falls in the same category as Warriner et al. An �indicates that the term falls into a different category than Warriner et al. Percentile bins were derived from the Warriner et al. corpus of almost 14,000 words. See text for further explication.

80

Table D-4

Descriptive Statistics for Valence Control Words in Study 1

Valence Control Words M SD n Warriner Norms

Healthy

8.42

.90

112

7.76 (1.58)

Peace

8.41

.99

112

7.75 (1.5)

Freedom

8.35

.94

112

7.72 (2.12)

Smile

8.27

1.11

112

7.89 (2.19)

Vacation

8.25

1.10

112

8.53 (0.77)

Succeed

8.19

1.02

112

7.05 (1.68)

Relax

8.14

1.06

112

7.82 (2.04)

Sunshine

8.09

1.21

112

8.14 (1.13)

Knowledgeable

7.69

1.24

112

7.95 (1.12)

Summer

7.59

1.65

112

7.50 (1.89)

Joke

7.43

1.53

112

7.88 (1.44)

table continues

81

Valence Control Words M SD n Warriner Norms

Dream

7.23

1.49

112

7.43 (1.8)

Give

7.12

1.49

112

7.73 (1.08)

Jail

1.54

.94

112

1.91 (1.44)

82

Table D-5

Descriptive Statistics for Arousal Control Words in Study 1

Arousal Control Words M SD n Warriner Norms

Emergency

8.29

1.20

76

6.43 (2.73)

Earthquake

8.25

1.11

76

6.76 (2.39)

Furious

8.25

1.12

76

6.09 (2.17)

Dangerous

8.12

1.02

76

6.81 (2.34)

Sex

8.04

1.35

76

7.6 (2.01)

Assault

8.00

1.27

76

6.8 (2.11)

Robber

7.75

1.17

76

6.2 (2.21)

Erotic

7.64

1.31

76

7.27 (2.51)

Suicide

7.54

1.65

76

6.21 (2.67)

Shotgun

7.47

1.33

76

6.55 (2.22)

Rock

3.97

2.34

76

3.14 (2.29)

table continues

83

Arousal Control Words M SD n Warriner Norms

Valley

3.24

1.75

76

2.7 (1.84)

Statue

2.67

1.73

76

5.95 (1.35)

Vegetable

2.67

1.83

76

3.75 (2.83)

84

Table D-6

Descriptive Statistics for Valence Calibrator Words in Study 1

Valence Calibrator Words M SD n Warriner Norms

Laughter

8.34

1.16

112

8.05 (1.57)

Accomplishment

8.20

1.02

112

8.05 (0.86)

Hug

7.97

1.37

112

8.23 (0.87)

Mechanic

5.23

1.41

112

5.45 (1.32)

Maintenance

4.75

1.15

112

5.95 (1.76)

Small

4.42

1.28

112

5.76 (2.02)

Leukemia

1.34

.94

112

1.47 (1.39)

Massacre

1.31

1.14

112

1.77 (1.57)

Terrorism

1.25

.72

112

1.60 (1.23)

85

Table D-7

Descriptive Statistics for Arousal Calibrator Words in Study 1

Arousal Calibrator Words M SD n Warriner Norms

Attack

7.82

1.26

76

7.05 (2.11)

Party

7.38

1.58

76

6.08 (2.80)

Rebellious

6.93

1.45

76

6.45 (1.93)

Eat

5.22

1.76

76

4.38 (2.79)

Soda

5.08

1.66

76

4.77 (2.27)

Cat

4.38

2.11

76

4.50 (2.48)

Breath

2.72

1.73

76

2.35 (1.90)

Tea

2.45

1.54

76

2.05 (1.43)

Meditation

1.42

.88

76

2.50 (1.99)

86

Table D-8

Summary of Descriptive Statistics for ABA Terms in Study 2

ABA Term in English ABA Term in Spanish

M

SD

t

p

Correlation Between

Spanish and English Ratings

r

Correlation Between

Difference Score and

Acculturation r

Correlation Between

Difference Score and Language

Preference (Angry)

r

Correlation Between

Difference Score and Language

Preference (Happy)

r

Positive Reinforcement Reforzamiento Positivo

7.23 7.24

1.39 1.59

-.06 .95 .56* .01 .13* .18

Satiation Saciedad

6.02 5.74

1.69 1.78

1.57 .12 .34* -.04 .01 .09

Stimulus Estimulo

5.82 5.78

1.47 1.38

.33 .74 .55* -.24** -.07 -.11

Motivating Operation Operación Motivacional

5.80 5.98

1.59 1.57

-1.14

.26 .40* -.00 -.15 .01

Escape Escapé

5.64 5.56

1.94 1.98

.48 .63 .46* -.01 -.00 -.07

Function Función

5.60 5.68

1.26 1.40

-.81 .42 .59* -.00 -.06 -.01

Behavior Conducta

5.56 5.49

1.32 1.22

.60 .55 .45* -.03 .02 .17

table continues

87

ABA Term in English ABA Term in Spanish

M

SD

t

p

Correlation Between

Spanish and English Ratings

r

Correlation Between

Difference Score and

Acculturation r

Correlation Between

Difference Score and Language

Preference (Angry)

r

Correlation Between

Difference Score and Language

Preference (Happy)

r

Reinforce Reforzar

5.52 5.68

1.50 1.76

-1.03

.31 .44* .07 .16 .01

Response Respuesta

5.49 5.73

1.30 1.29

-1.82

.07 .35* -.02 -.09 .01

Shaping Moldeamiento

5.38 5.06

1.22 1.27

2.09 .04 -.01 .04 .02 -.02

Preference Assessment Evaluación de Preferencias

5.36 4.76

1.41 1.22

3.97 .001 .21* -.07 -.06 -.05

Establishing Operation Operación de Establecimiento

5.31 5.32

1.26 1.41

-.06 .95 .35* .05 .07 -.00

Target Behavior Conducta de Interes

5.25 5.48

1.61 1.44

-1.63

.11 .43 .09 .02 -.02

Elopement Conducta de Fuga

5.25 3.98

1.80 1.53

5.92 .001 -.04 .01 -.04 .04

Function of Behavior Función de la Conducta

5.22 5.31

1.38 1.32

-.75 .46 .44* .11 -.02 -.02

Operational Definition Definición Operacional

5.15 5.17

1.23 1.22

-.15 .89 .50* .05 .14 .12

Brief Functional Analysis Analisis Funcional Breve

5.10 5.11

1.26 1.10

-.13 .89 .36* -.04 -.00 -.10

table continues

88

ABA Term in English ABA Term in Spanish

M

SD

t

p

Correlation Between

Spanish and English Ratings

r

Correlation Between

Difference Score and

Acculturation r

Correlation Between

Difference Score and Language

Preference (Angry)

r

Correlation Between

Difference Score and Language

Preference (Happy)

r

Task Analysis Analisis de Tarea

5.07 4.95

1.48 1.48

.96 .34 .55* .08 .00 -.02

Token Economy Economia de Fichas

4.86 4.91

1.34 1.32

-.42 .68 .36* .03 .06 -.05

Contingency Contingencia

4.86 4.84

1.54 1.47

.99 .92 .27* .03 -.02 -.14

Reinforcement Schedule Programa de Reforzamiento

4.85 5.11

1.55 1.70

-1.62 .11 .38* .14 .14* .23

Antecedent Antecendente

4.84 4.75

1.24 1.33

.77 .45 .41* .02 -.04 -.05

Early Intensive BI Intervención Conductal TI

4.70 4.58

1.33 1.61

.82 .42 .49* -.01 -.02 -.05

Generalization Generelización

4.69 4.94

1.58 1.37

-1.99 .05 .54* -.04 -.09 -.17

Differential Reinforcement Reforzamineto Diferecial

4.62 4.91

1.43 1.33

-2.14 .03 .38* -.12 -.03 -.05

Chain Cadena

4.23 4.22

1.65 1.73

.06 .95 .58* .00 .03 .05

Delayed Reinforcement Reforzamiento Demorado

4.10 4.29

1.66 1.61

-1.07 .29 .26* .12 .01 -.02

table continues

89

ABA Term in English ABA Term in Spanish

M

SD

t

p

Correlation Between

Spanish and English Ratings

r

Correlation Between

Difference Score and

Acculturation r

Correlation Between

Difference Score and Language

Preference (Angry)

r

Correlation Between

Difference Score and Language

Preference (Happy)

r

Time-Out Tiempo Fuera

4.09 4.52

1.88 1.95

-2.30 .02 .38* -.02 -.05 -.09

Consequence Consecuencia

4.02 4.02

1.88 1.81

.00 1.00 .47* -.17 -.04 -.15

Stereotypy Estereotipia

3.60 3.88

1.80 1.82

-1.67 .10 .44* .02 .09 .12

Incompatible Behavior Conducta Incompatible

3.00 3.29

1.52 1.55

-2.11 .04 .48* .13 .08 -.03

Negative Reinforcement Reforzamiento Negativo

2.60 2.57

1.70 1.72

.26 .80 .68* .08 -.10 -.06

Deprivation Privación

2.33 4.01

1.62 2.25

-7.38 .001 .16 -.01 -.15 -.15

Extinction Extinción

2.25 2.35

1.88 1.92

-.87 .39 .75* -.02 .09 .04

Punishment Castigo

2.22 2.40

1.62 1.78

-1.15 .25 .50* -.01 -.04 .01

Discrimination Discriminación

1.86 2.03

1.41 1.38

-1.57 .12 .60* .04 -.01 .04

* p < .05 ** p < .001

90

Table D-9

Summary of Descriptive Statistics for General Psychological Terms in Study 2

General Psychological Term

M

SD

t

p

Correlation Between

Spanish and English Ratings

r

Correlation Between

Difference Score and

Acculturation r

Correlation Between

Difference Score and Language

Preference (Angry)

r

Correlation Between

Difference Score and Language

Preference (Happy)

r

Reward Recompensa

8.00 7.06

1.28 1.77

6.27 .001 .43** .13 .13 .13

Praise Alabanza

7.53 6.68

1.55 1.91

4.98 .001 .39** .04 .24** .12

Incentive Incentivo

6.82 6.94

1.82 1.67

-.79 .43 .59** .04 .09 .03

Empathy Empatia

6.71 6.71

2.07 1.77

-.05 .96 .56** .03 .05 .05

Feeling Sentimiento

6.06 6.18

1.61 1.77

-.74 .46 .44** -.10 -.04 .01

Play Therapy Terapia Ludica

5.98 5.44

1.44 1.76

3.37 .001 .46** -.15 -.22* -.13

Emotion Emoción

5.96 6.27

1.57 1.47

-2.56 .01 .63** -.01 .10 .12

Plan Plan

5.94 6.25

1.38 1.47

-2.48 .01 .52** .11 .03 .01

table continues

91

General Psychological Term

M

SD

t

p

Correlation Between

Spanish and English Ratings

r

Correlation Between

Difference Score and

Acculturation r

Correlation Between

Difference Score and Language

Preference (Angry)

r

Correlation Between

Difference Score and Language

Preference (Happy)

r

Confidentiality Confidencial

5.90 5.87

1.67 1.59

.24 .81 .58** .11 .02 .06

Obedience Obediente

5.63 6.03

1.93 1.73

-3.19 .001 .70** -.00 .01 .00

Treatment Tratamiento

5.61 5.44

1.56 1.21

1.20 .23 .33** -.06 -.00 -.01

Therapy Terapia

5.60 5.58

1.71 1.59

.12 .91 .59** .06 -.15 -.06

Adjustment Ajuste

5.57 5.40

1.45 1.23

1.31 .19 .44** -.07 -.15 -.03

Counseling Asesoramiento

5.40 5.57

1.74 1.31

-1.12 .26 .36** -.13 -.07 -.08

Client Cliente

5.38 5.58

1.46 1.46

-1.83 .07 .65** -.04 -.16 -.17

Mood Animo

5.37 7.13

1.47 1.74

-9.78 .001 .20* .07 .12 .12

Referral Referencia

5.33 5.33

1.47 1.28

.00 1.00 .33** -.05 -.11 -1.0

table continues

92

General Psychological Term

M

SD

t

p

Correlation Between

Spanish and English Ratings

r

Correlation Between

Difference Score and

Acculturation r

Correlation Between

Difference Score and Language

Preference (Angry)

r

Correlation Between

Difference Score and Language

Preference (Happy)

r

Behavior Modification Modificación de Comportamiento

4.83 4.88

1.49 1.67

-.43 .67 .59** .07 .19* .14

Risk Factors Factores de Riesgo

3.75 3.81

1.78 1.60

-.29 .77 .21* 1.0 .06 .02

Learned Helplessness Indefensión apredinda

3.35 4.05

1.93 1.73

-3.33 .001 .22* -.14 -.05 -.24**

Denial Negación

2.90 2.90

1.64 1.64

.05 .96 .37** .05 .02 1.0

Delusion Delirante

2.79 3.90

1.79 1.92

-5.73 .001 .31** -.04 -.04 -.13

Tantrum Berrinche

2.67 2.75

1.89 1.79

-.45 .65 .42** -.05 -.21* -.18*

Disorder Trastorno

2.44 2.81

1.59 1.88

-2.01 .04 .37** -.15 -.09 -1.0

Chronic Stress Estresores Cronicos

2.39 2.62

1.70 1.76

-1.45 .15 .51** -.08 -.16 -.12

Penalty Castigo

2.33 2.27

1.57 1.72

.35 .73 .40** .00 -.13 .03

Prejudice Prejucio

2.31 2.51

1.66 1.72

-1.70 .09 .70** .08 -.01 .02

Anxiety Anciedad

2.09 2.40

1.52 1.60

-2.13 .04 .45** -.04 -.06 -.11

table continues

93

General Psychological Term

M

SD

t

p

Correlation Between

Spanish and English Ratings

r

Correlation Between

Difference Score and

Acculturation r

Correlation Between

Difference Score and Language

Preference (Angry)

r

Correlation Between

Difference Score and Language

Preference (Happy)

r

Addiction Adicción

2.06 2.03

1.76 1.44

.28 .78 .70** .01 -.06 -.06

Stress Estres

2.01 2.27

1.47 1.56

-2.00 .05 .53** -.04 -.03 -1.0

Substance Abuse Abusos de Sustancias

1.85 1.90

1.34 1.52

-.45 .65 .54** .06 .00 -.07

Depression Depresión

1.48 1.59

1.26 1.10

-1.03 .30 .57** -.01 -.04 -.12

* p < .05 ** p < .001

94

Table D-10

Summary of Descriptive Statistics for Control Words in Study 2

Control Words

M

SD

t

p

Correlation Between

Spanish and English Ratings

r

Correlation Between

Difference Score and

Acculturation r

Correlation Between

Difference Score and Language

Preference (Angry)

r

Correlation Between

Difference Score and Language

Preference (Happy)

r

Vacation Viaje

8.27 7.48

1.21 1.70

5.79 .001 .50** -.00 .08 -.04

Freedom Libre

8.20 7.96

1.46 1.54

1.98 .05 .59** -.01 -.05 .03

Healthy Sano

8.21 7.59

1.31 1.83

4.52 .001 .55** .02 .16 .06

Smile Sonreir

8.08 8.12

1.47 1.35

-.32 .75 .50** .05 .07 .11

Succeed Triunfar

8.06 7.68

1.40 1.87

2.47 .02 .47** .03 .11 .03

Sunshine Soleado

7.96 6.68

1.43 2.16

6.89 .001 .38** .01 .05 .06

Relax Relajar

7.94 7.77

1.39 1.53

1.61 .11 .68** .02 .01 -.05

table continues

95

Control Words

M

SD

t

p

Correlation Between

Spanish and English Ratings

r

Correlation Between

Difference Score and

Acculturation r

Correlation Between

Difference Score and Language

Preference (Angry)

r

Correlation Between

Difference Score and Language

Preference (Happy)

r

Summer Verano

7.75 7.61

1.49 1.62

1.56 .12 .79** -.03 .16 .10

Knowledgeable Sabiduria

7.48 7.10

1.55 1.71

2.59 .01 .51** .15 .20* .07

Joke Chiste

7.43 7.52

1.47 1.72

-.64 .52 .47** -.09 -.07 .03

Dream Soñar

7.32 6.80

1.59 1.70

3.64 .001 .53** -.04 -.07 -.08

Give Regalar

7.18 6.87

1.58 1.70

2.02 .05 .45** .19* .02 -.04

Jail Carcel

1.74 2.04

1.45 1.63

-2.36 .02 .57** -04 -.09 .02

* p < .05 ** p < .001

96

Table D-11

Summary of Descriptive Statistics for Calibrator Words in Study 2

Calibrator Words

M

SD

t

p

Correlation Between

Spanish and English Ratings

r

Correlation Between

Difference Score and

Acculturation r

Correlation Between Difference

Score and Language

Preference (Angry) r

Correlation Between

Difference Score and Language

Preference (Happy)

r

Laughter Risa

8.12 7.94

1.43 1.62

1.19 .24 .37** .04 -.07 .05

Hug Abrazo

8.05 7.95

1.33 1.51

.66 .51 .35** .07 .12 .18*

Accomplishment Logro

7.96 7.50

1.51 1.77

3.23 .002 .54** .16 .05 .08

Mechanic Mecanico

5.28 5.23

1.21 1.25

.49 .63 .60** .03 -.01 -.09

Maintenance Mantenimiento

5.25 5.53

1.49 1.40

-2.19 .03 .51** -.06 -.08 -.02

Small Pequeño

4.79 5.20

1.48 1.41

-2.55 .01 .24** -.04 -.05 -.04

Massacre Masacre

1.44 1.55

1.38 1.15

1.10 .27 .61** .02 -.02 -.02

table continues

97

Calibrator Words

M

SD

t

p

Correlation Between

Spanish and English Ratings

r

Correlation Between

Difference Score and

Acculturation r

Correlation Between Difference

Score and Language

Preference (Angry) r

Correlation Between

Difference Score and Language

Preference (Happy)

r

Terrorism Terrorismo

1.44 1.47

1.27 1.17

-.20 .84 .38** -.10 -.02 -.12

Leukemia Leucemia

1.40 1.70

.98 1.39

-2.49 .01 .41** .12 .06 .15

* p < .05 ** p < .001